Ingram School of Engineering

CE 1210. Introduction to Smart Infrastructure.

This course examines municipal and private infrastructure systems with emphasis on smart technologies for monitoring and management. Topics include transportation, water resources, environmental, geotechnical, structural, and material systems. Case-based analyses highlight asset performance, sensing technologies, and data-driven decision-making in infrastructure management. The course also addresses system integration, lifecycle considerations, and resilience in infrastructure planning and operation. Additional focus is placed on the roles and professional responsibilities of civil engineers in planning, design, and operation of infrastructure systems within societal and environmental contexts.

CE 2340. Infrastructure Materials.

This course examines the properties and behavior of infrastructure materials, including cement concrete, asphalt concrete, wood, and steel. Emphasis is placed on the composition and characteristics of cement concrete constituents and their influence on fresh and hardened properties. Material behavior is analyzed in relation to performance, durability, and structural applications. The course also provides an overview of other commonly used infrastructure materials and their roles in engineering systems. Applications consider standard practices and material selection in civil engineering contexts. Prerequisite: CHEM 1335 and ENGR 3311 with grades of "C" or better.

CE 2350. Structural Analysis.

This course examines the analysis of structures subjected to various loading conditions. Determinate and indeterminate structures are analyzed using classical and modern computational methods. Structural response is evaluated in terms of reactions, internal forces, and deformations. Structural idealization, modeling assumptions, and solution procedures are addressed to support the analysis of structural systems. Emphasis is placed on the interpretation and verification of results and on the application of analysis techniques to practical structural engineering problems commonly encountered in engineering practice. Prerequisite: ENGR 3311 with a grade of "C" or better.

CE 3310. Applications in Smart Infrastructure.

This course presents and immerses students in various realistic civil engineering scenarios centered on diverse infrastructure assets. Each student applies analytical techniques to process civil engineering data and make informed decisions based on their data analysis findings. In addition, students collaborate in teams to explore both state-of-the-art and industry-standard smart infrastructure sensor technologies. They learn to collect, transmit, and analyze data, ultimately using these insights to design and propose effective engineering solutions tailored to specific project challenges in the real-world engineering applications. Prerequisite: CE 1210 and CS 1342 and ENGR 3373 with grades of "C" or better.

CE 3320. Environmental Engineering.

This course introduces fundamental principles of environmental engineering with an emphasis on water resources and water quality management. Topics include material balances, hydrologic processes, water chemistry, drinking water treatment, wastewater treatment, and water pollution, with brief coverage of air quality, solid waste, and hazardous materials. Students engage in quantitative problem-solving, laboratory analysis, and evaluation of environmental systems. By the end of the course, students are expected to apply engineering principles to assess environmental problems and identify appropriate treatment and management approaches. Prerequisite: CHEM 1335 and [(BIO 1130 and BIO 1330) or (BIO 1131 and BIO 1331) or GEOL 1410] with grades of "C" or better.

CE 3330. Soil Mechanics.

This course examines the fundamental engineering properties and mechanical behavior of soils relevant to geotechnical analysis and design. Topics include soil composition, soil classification, phase relationships, compaction characteristics, hydraulic conductivity and seepage analysis, Mohr’s circles, the principle of effective stress, shear strength, consolidation theory, and stress–strain relationships under loading. Students conduct standard laboratory testing methods in accordance with ASTM specifications to characterize soil behavior. The course emphasizes quantitative analysis, data interpretation, and visualization techniques applied to the evaluation of geotechnical systems. Prerequisite: ENGR 3311 with a grade of "C" or better.

CE 3331. Infrastructure Foundations.

This course introduces the principles and practices of foundation engineering, with emphasis on the design of shallow and deep foundations. Topics include site investigation methods, geotechnical data interpretation, and bearing capacity and settlement analysis applied to real-world problems. Foundations are evaluated for consolidation, rate of settlement, stress distribution, elastic settlement, and bearing capacity. The course examines the design and performance of spread footings, mat foundations, pile foundations, and drilled shafts, along with methods for estimating load transfer and evaluating construction impacts. Additional emphasis is placed on foundation life-cycle management, constructability considerations, and modern design standards used in professional civil engineering practice. Prerequisite: CE 3330 with a grade of "C" or better.

CE 3350. Design of Reinforced Concrete Infrastructure.

This course covers the analysis and design of reinforced concrete infrastructure systems. Topics include the analysis and design of singly and doubly reinforced beams, one-way slabs, and columns. Emphasis is placed on structural behavior, analytical methods, fundamental design principles, and failure mechanisms. Students develop the ability to read, interpret, and apply relevant design codes and specifications. In addition, the course introduces modern technologies for monitoring structural behavior, supporting performance evaluation and condition assessment of reinforced concrete infrastructure in real-world applications. Prerequisite: CE 2340 and CE 2350 with grades of "C" or better.

CE 3360. Introduction to Transportation Engineering.

This course is an introduction to the planning and design of transportation infrastructure assets. Social, economic, safety, and engineering issues impacting transportation are examined. Interactions between users, vehicles, and the infrastructure are addressed. The expanding use of technology to enhance transportation systems are examined. Topics covered in this course include geometric design of roadways, traffic flow theory, queuing analysis, traffic data collection, traffic safety, intersection design, and traffic signal timing, and emerging technologies in transportation. Prerequisite: IE 3320 with a grade of "C" or better.

CE 4100. Civil Engineering Undergraduate Research.

This course introduces students to the fundamental structure and content of undergraduate research in civil engineering, focusing on basic concepts and guided learning. The instructor covers simple approaches to identifying research topics, conducting literature reviews, and applying basic research methods. Instruction includes regular meetings, guided readings, and structured activities in key civil engineering areas such as environmental, geotechnical, material, structural, transportation, and water resources engineering. Emphasis focuses on building fundamental skills in technical writing, data interpretation, and presentation. The instructor provides close supervision and step-by-step guidance to support student learning and ensure clear understanding of essential research concepts. Prerequisite: Instructor Approval.

CE 4200. Civil Engineering Undergraduate Research.

This course builds on foundational research skills in civil engineering, guiding students to refine research questions, explore literature more critically, and apply structured methods to investigate defined topics. Instruction covers data collection techniques, basic analytical tools, and interpretation of results within core civil engineering areas. Students engage in guided project development, critical evaluation of sources, and structured writing tasks. Emphasis focuses on strengthening technical communication, improving analytical thinking, and developing organized research workflows. The instructor provides continued supervision while encouraging greater independence and deeper engagement with research content. Prerequisite: Instructor Approval.

CE 4300. Civil Engineering Undergraduate Research.

This course advances students’ skills in civil engineering research by engaging them in independent, in-depth research. The instructor guides students through advanced research design, comprehensive literature analysis, and complex data interpretation. Instruction covers contemporary challenges and specialized topics such as structural, environmental, water resource, transportation, materials, and geotechnical engineering. Students strengthen professional skills in technical writing, oral presentations, and ethical research practices while managing research projects independently. Emphasis focuses on critical thinking, problem-solving, and the application of rigorous methodologies to produce high-quality, well-documented research outcomes. Students also learn to evaluate and integrate multidisciplinary perspectives to address real-world engineering problems. Prerequisite: Instructor Approval.

CE 4310. Infrastructure Sensor Technologies.

This course examines advanced sensor technologies used to monitor the performance and behavior of infrastructure assets. Topics include surveying and sensing systems such as auto level, total station, Global Positioning System (GPS), mobile and static LiDAR, and 3D imaging technologies. The course analyzes data acquisition principles, sensor accuracy, and sources of uncertainty in infrastructure monitoring. Students analyze and interpret sensor data using commonly adopted software tools. Applications across transportation, geotechnical, structural, and environmental systems are examined through practical use of sensing technologies and real-world case studies. The course also evaluates the integration of sensing systems into infrastructure management and decision-making processes. Prerequisite: CE 3310 with a grade of "C" or better.

CE 4320. Biological Wastewater Treatment.

This course examines the biological treatment processes for domestic wastewater, including sludge processing and disposal. The students analyze the biological principles and theory behind modern wastewater treatment. The students examine the design biological wastewater treatment processes to remove typical domestic contaminants and nutrients. The students also examine advances in resource recovery from wastewater. The students experience the calibration and application of modern computer modeling software for the sizing and troubleshooting of wastewater treatment processes. Prerequisite: CE 3320 with a grade of "C" or better.

CE 4321. Hazardous Waste Management.

This course examines best management practices for hazardous waste. Topics include contamination processes, site investigation techniques, detection strategies, analytical methods, evaluation approaches, risk management principles, and treatment protocols. Students explore how technology supports the full life cycle management of contaminated hazardous waste sites, from identification and assessment through remediation and long term monitoring. Emphasis focuses on practical applications, regulatory considerations, and sustainable solutions for protecting human health and the environment while addressing evolving industry standards and emerging challenges. Prerequisite: CE 3320 with a grade of "C" or better.

CE 4323. Physical and Chemical Treatment of Water.

This course examines physical and chemical processes used in drinking water treatment with an emphasis on engineering design and regulatory compliance. Topics include source water characteristics, conventional treatment processes (coagulation, flocculation, sedimentation, filtration, and disinfection), membrane systems, and advanced treatment technologies, along with applicable drinking water regulations. Students engage in quantitative analysis and design of treatment units, including reactors, basins, filters, and pumping systems. By the end of the course, students are expected to design and evaluate drinking water treatment processes that achieve regulatory compliance and protect public health. Prerequisite: CE 3320 with a grade of "C" or better.

CE 4330. Design of Retaining Structures.

This course examines the geotechnical analysis and design of earth retaining structures. Topics include lateral earth pressure theories such as at-rest pressures, Rankine active pressures, and Rankine passive pressures, as applied to the design of internally, externally, and hybrid stabilized retaining systems. Additional topics include modes of instability, remediation methods for failing retaining structures, and the use of technology for asset management. The course addresses analysis and design considerations relevant to the life-cycle performance of earth retaining systems. Corequisite: CE 3331 with a grade of "C" or better.

CE 4340. Pavement Design and Evaluation.

This course examines the design, construction, evaluation, and rehabilitation of highway pavements through an integrated framework. Fundamental aspects of pavement systems—including material characterization, structural design, and performance evaluation—are analyzed for both concrete and asphalt pavements. Emphasis is placed on mechanistic-empirical design approaches, distress identification, and maintenance and rehabilitation strategies. The course also considers sustainability, durability, and life-cycle performance in pavement engineering. Applications incorporate real-world examples, case studies, and design tools to support analysis of current practices and emerging developments in professional engineering contexts. Prerequisite: CE 2340 and ENGR 3311 with grades of “C” or better.

CE 4350. Design of Prestressed Concrete Infrastructure.

This course covers the analysis and design of prestressed concrete infrastructure systems. Topics include prestressed beams, slabs, and columns. Emphasis is placed on structural behavior, prestress losses, and fundamental design principles under service and ultimate limit states. Students develop the ability to read, interpret, and apply relevant design codes and specifications. In addition, the course introduces modern technologies for monitoring structural behavior, supporting performance evaluation and condition assessment of prestressed concrete members in real-world engineering applications. Prerequisite: CE 3350 with a grade of "C" or better.

CE 4351. Design of Steel Infrastructure.

This course covers the analysis and design of structural members and connections of steel structures according to professional design standards and specifications. Topics include limit states in design and the probabilistic nature of loads and resistance, design of members subjected to tension, axial compression, bending and combined forces in steel structures, introduction of analysis and design of steel frames with secondary effects, design of steel structures for stability, and design of steel connections using bolts and welds with various loading conditions. Prerequisite: CE 2350 with a grade of "C" or better.

CE 4360. Intelligent Transportation Systems.

This course is a study of components, technologies, and infrastructure assets that comprise intelligent transportation systems (ITS). Smart technologies, data acquisition, and communication sub-systems are examined within the context of personal, commercial, and public transportation. Coverage includes mobility, public safety, socio-economic and environmental factors impacting transportation systems. There are three main themes discussed in this course: data collection and monitoring using ITS; modeling and analysis using ITS data; and operations, control and management using ITS data. Prerequisite: CE 3310 and CE 3360 with grades of "C" or better.

CE 4361. Highway Engineering.

This course integrates fundamental concepts of traffic engineering and pavement engineering for the design, operation, and maintenance of highway systems. Topics include traffic flow theory, signal timing, intersection design, highway capacity, traffic control devices, and safety considerations. Pavement engineering topics cover materials, subgrade characterization, and both flexible and rigid pavement design, including thickness design, performance evaluation, and maintenance strategies. The course also introduces basic data analysis from traffic sensing and pavement condition monitoring systems. Emphasis is placed on developing practical engineering skills and applying standard methods to real-world roadway design and operational problems. Prerequisite: CE 3360 with a grade of "C" or better.

CE 4362. Traffic Engineering.

This course introduces the components of highway traffic systems and the fundamentals of traffic engineering. Topics include analysis of traffic stream characteristics, level of service, and capacity of urban and rural highways. Methods of traffic data collection using fixed and mobile sources are examined, along with macroscopic and microscopic traffic modeling. The course also covers warrants for traffic control devices and the design and analysis of traffic signals and timing plans. Applications include the analysis of urban and highway traffic characteristics using empirical data and simulation software. Prerequisite: CE 3360 with a grade of ’C’ or better.

CE 4370. Hydraulics.

This course examines the properties, distribution, and circulation of water in natural and engineered systems. Topics include pipe flow, pipe networks, pumps, and open channel flow. Students analyze fluid behavior within these systems and evaluate performance under varying conditions. The course introduces advanced data analysis and visualization techniques to interpret system performance. Emphasis focuses on practical applications, system design considerations, and modern tools used to improve efficiency, reliability, and sustainability in water distribution and management systems. Prerequisite: ENGR 3380 with a grade of "C" or better.

CE 4371. Hydrology.

This course examines the fundamental principles of hydrology and their application to water resources management. The global and regional water cycle, including precipitation, infiltration, evapotranspiration, and runoff processes, is investigated at multiple spatial scales. Rainfall-runoff relationships, flood frequency analysis, and flow routing methods are explored to address water-related engineering challenges. Stormwater design, including detention basin sizing and urban runoff management, is covered in the context of sustainable infrastructure planning. Computational hydrologic models and sensor-based monitoring technologies are examined to support quantitative analysis for water resources design. Prerequisite: ENGR 3380 with a grade of "C" or better.

CE 4390. Civil Engineering Design I.

This course is the first in a two-course sequence designed to prepare students for engineering practice through a culminating major design experience. It covers the planning, scheduling, budgeting, and management aspects of a technology-enhanced infrastructure design project. Students are assigned a civil infrastructure problem and develop multiple solution alternatives, which are evaluated using established criteria such as capital cost, life-cycle cost, sustainability, constructability, and operational considerations. Emphasis is placed on structured decision-making and project organization in the context of civil engineering design. Prerequisite: CE 3330 with a grade of "C" or better. Corequisite: CE 3310 and CE 3350 and CE 3360 with grades of "C" or better.

CE 4391. Civil Engineering Design II.

This course is the second in a two-course sequence meant to prepare students for engineering practice with a culminating major design experience. The students focus on the completion of design of the infrastructure proposed in the first course. Students select design elements of the infrastructure and apply previous knowledge to produce engineering drawings and diagrams. The design elements explored include, but are not limited to, foundations, structural analysis, hydrology and hydraulics (H&H), biological processes, chemical processes, pavement, site layout and grading etc. Prerequisite: CE 3320 and CE 4390 with grades of "C" or better. Corequisite: CE 3331 and CE 4370 with grades of "C" or better.

CE 4392. Sustainable Infrastructure.

This course examines the characteristics and performance of infrastructure systems in relation to resource use, durability, and life-cycle considerations. Topics include infrastructure materials, design approaches, and asset management strategies that influence long-term performance. Examples of applications include pervious pavements, alternative construction materials, and approaches to infrastructure design that account for environmental and operational factors. The course analyzes methods used to evaluate and manage infrastructure over its service life, including the use of technology to monitor condition and support decision-making. Emphasis is placed on frameworks and tools used to assess infrastructure systems across planning, design, and maintenance stages. Prerequisite: ENGR 3311 and ENGR 3315 with grades of "C" or better.

EE 2100. Circuits I Lab.

This course examines the principles of circuit analysis through practical measurement and experimentation of direct current and voltage. Students analyze the behavior of resistive, capacitive, and inductive circuits using standard measurement techniques and instrumentation. Inquiry focuses on the application of fundamental theorems to diverse circuit configurations and the design of experimental procedures. Students examine the DC and AC analysis of electrical systems to evaluate theoretical models against physical data. Analysis includes the use of computer-aided tools for circuit implementation and the verification of system performance. Students investigate the impact of component tolerances and measurement errors on overall analytic accuracy. This exploration provides a framework for evaluating the electric system design. Prerequisite: MATH 2471 with a grade "C" or better. Corequisite: EE 2300 with a grade "C" or better.

EE 2120. Digital Logic Lab.

This course examines the principles of digital logic design through the implementation and analysis of discrete components and logic devices. Students analyze combinational logic circuits, including encoders, decoders, and multiplexers, to evaluate Boolean algebraic expressions and minimization techniques. Inquiry focuses on the design and verification of sequential logic systems such as flip-flops, counters, and registers. Students examine the behavior of finite state machines and their application in synchronous and asynchronous digital systems. Analysis includes the use of hardware description languages to simulate and synthesize digital architectures on integrated circuits. Students investigate the impact of propagation delays, timing constraints, and power consumption on system reliability. Discussions evaluate the transition from theoretical logic gates to physical hardware realization within modern electronic frameworks. Systematic evaluation of these elements provides a foundation for the architectural design of complex processing units. Corequisite: CS 1428 and EE 2320 with grades of "C" or better.

EE 2300. Circuits I.

This course examines the fundamental concepts of electric circuit analysis, including Kirchhoff’s laws, Ohm’s law, and basic network theorems. Students analyze resistive circuits using nodal and mesh analysis techniques to evaluate current and voltage distributions within complex networks. Inquiry focuses on the behavior of energy storage elements, specifically capacitors and inductors, within first-order RL and RC circuits. Analysis includes the study of power calculations, maximum power transfer, and the response of circuits to constant and time-varying sources. Students investigate the characteristics of steady-state direct current systems and the transient behavior of switched networks. Evaluation of these circuit properties provides a technical foundation for the modeling and design of modern electrical systems. Prerequisites: MATH 2471 with a grade of "C" or better. Corequisites: EE 2100 with a grade "C" or better.

EE 2320. Digital Logic.

This course examines the fundamental principles of digital systems through the study of Boolean algebra, logic gates, and number representation. Students analyze combinational logic design techniques, including minimization using Karnaugh maps and the implementation of arithmetic circuits. Inquiry focuses on the design and operation of sequential logic elements such as latches, flip-flops, and counters. Students examine the architecture of finite state machines and their role in controlling complex digital processes. Analysis includes the investigation of synchronous and asynchronous timing, propagation delays, and memory organization within digital architectures. These concepts lay the groundwork for understanding the hierarchical layers within modern computing hardware and support the design of robust electronic systems. Corequisites: CS 1428 and EE 2120 with a grade of "C" or better.

EE 3100. Instrumentation Laboratory.

This course examines the principles of modern measurement systems and the characterization of electronic instrumentation. Students analyze the performance of various sensors and transducers used to convert physical phenomena into electrical signals. Inquiry focuses on signal conditioning techniques, including amplification, and filtering to ensure data integrity. Students examine the impact of noise, resolution, and sensitivity on measurement accuracy within complex data acquisition systems. Analysis includes the statistical evaluation of experimental data and the application of error analysis to determine system reliability. Students investigate the integration of computer-aided tools for real-time monitoring and control of physical processes. Evaluation of these instrumentation architectures identifies the relationship between hardware precision and analytical results. Systematic inquiry into measurement theory provides a framework for the development of sophisticated diagnostic and monitoring tools. Prerequisite: EE 2300 and MATH 3323 with grades of "C" or better. Corequisite: EE 3300 with grade of "C" or better.

EE 3120. Microprocessors Lab.

This course examines the architecture and programming of microprocessors and microcontrollers within embedded systems. Students analyze instruction sets, addressing modes, and the execution of assembly and high-level language programs. Inquiry focuses on the interfacing of processing units with external hardware, including sensors, actuators, and communication modules. Students examine the behavior of interrupts, timers, and input/output ports during real-time system operation. Analysis includes the implementation of memory mapping and the evaluation of bus architectures for efficient data transfer. Students investigate the impact of clock speed, power consumption, and peripheral integration on system performance. Evaluation of these hardware-software interactions identifies the relationship between low-level code and physical device control. Systematic inquiry into embedded logic provides a framework for the development of integrated processing platforms. Prerequisite: EE 2320 and EE 2120 with grades of "C" or better. Corequisite: EE 3320 with a grade of "C" or better.

EE 3150. Microelectronics Laboratory.

This course examines the characterization and application of semiconductor devices including diodes, bipolar junction transistors, and field-effect transistors. Students analyze the operation of single-stage and multi-stage amplifiers to evaluate voltage gain, input/output impedance, and frequency response. Inquiry focuses on the design of biasing networks and the implementation of small-signal models for signal processing applications. Students examine the behavior of operational amplifiers and their internal integrated circuit architectures within various feedback configurations. Analysis includes the impact of non-ideal characteristics, such as saturation, parasitic capacitance, and thermal effects, on overall circuit performance. Students investigate the integration of discrete components into complex analog systems to verify theoretical models against physical data. Evaluation of these microelectronic structures identifies the fundamental relationship between device physics and functional circuit design. Systematic inquiry into electronic hardware supports the development of precision signal conditioning and processing units. Prerequisite: EE 3300 and EE 3100 with grades of "C" or better. Corequisite: EE 3350 with a grade of "C" or better.

EE 3300. Circuits II.

This course examines advanced alternating current circuit analysis, including phasors, impedance, and sinusoidal steady-state response. Students analyze complex power, power factor correction, and the operation of three-phase systems within power distribution networks. Inquiry focuses on the application of Laplace transforms to evaluate the transient and steady-state responses of higher-order linear circuits. Students examine the frequency response of electrical networks, incorporating the design of passive filters and resonant systems. Analysis includes the study of magnetically coupled circuits, transformers, and two-port network parameters for comprehensive system modeling. Students investigate the relationship between pole-zero locations and circuit stability. Evaluation of frequency-domain techniques provides a framework for analyzing signal transmission and power conversion. Systematic inquiry into network theory supports the development of robust electrical architectures. Prerequisites: EE 2300 and EE 2100 and MATH 3323 with grades of "C" or better. Corequisites: EE 3100 with grade of "C" or better.

EE 3320. Microprocessors.

This course examines the architecture and operation of microprocessors, focusing on computing hardware and digital logic. Students analyze assembly language programming and instruction set execution to evaluate interactions between hardware and software. Topics include timing analysis, input/output interfacing, memory organization, bus structures, and interrupt-driven communication. Students investigate embedded system components, including peripheral integration and real-time processing considerations. Emphasis is placed on analyzing hardware-software interfaces and evaluating system performance using concepts such as caching and pipelining. Prerequisites: EE 2320 and EE 2120 with a grade of "C" or better. Corequisites: EE 3120 with a grade of "C" or better.

EE 3326. Numerical and Scientific Data Analysis Using Python.

This course examines Python programming through the application of numerical and scientific computing libraries tailored for engineering analysis. Students analyze fundamental syntax and data structures to develop efficient computational algorithms. Inquiry focuses on the implementation of NumPy for multidimensional array processing and linear algebra operations. Students examine scientific computing methodologies using SciPy to solve complex mathematical problems involving integration, optimization, and signal processing. Analysis includes data manipulation techniques using Pandas for structured dataset management and statistical evaluation. Students investigate data visualization frameworks such as Matplotlib to interpret and communicate engineering results through graphical representation. Discussions evaluate the principles of object-oriented programming to create modular and scalable software architectures for technical applications. Systematic inquiry into these computational tools provides a framework for automating data-driven engineering tasks. Prerequisite: CS 1342 or CS 1428 with a grade of "C" or better.

EE 3340. Electromagnetics.

This course examines the fundamental principles of electromagnetic field theory and its application to high-frequency systems. Students analyze Maxwell’s equations in both differential and integral forms to evaluate the behavior of electric and magnetic fields in diverse media. Inquiry focuses on wave propagation characteristics, including reflection, refraction, and polarization within unbounded and bounded regions. Students examine the theory of transmission lines through the study of Smith charts, impedance matching, and transient analysis. Analysis includes the operation of wave guides and the fundamental parameters of antenna systems for wireless communication. Students investigate the interaction between electromagnetic waves and material boundaries to determine energy distribution and power flow. Evaluation of these electrodynamic concepts identifies the physical constraints of signal transmission. Systematic inquiry into field theory provides a framework for the design of microwave and radio frequency components. Prerequisite: [EE 3300 or EE 3400] and MATH 2393 and PHYS 2326 and PHYS 2335 with grades of "C" or better.

EE 3350. Microelectronics.

This course examines the analysis and design of active device equivalent circuits with a focus on semiconductor technologies. Students analyze the operation of bipolar junction and field-effect transistors within various circuit topologies to evaluate small-signal and large-signal behaviors. Inquiry focuses on the implementation of operational amplifiers and their integrated circuit architectures for signal processing applications. Students examine the principles of feedback and its impact on gain stability, bandwidth, and input/output impedance. Analysis includes the frequency response of multi-stage amplifiers and the design of switching circuits for digital and power electronic functions. Students investigate the relationship between physical device parameters and functional system performance within integrated environments. Evaluation of these microelectronic structures identifies the trade-offs between speed, power consumption, and linearity. Systematic inquiry into active device modeling provides a framework for the development of modern analog and mixed-signal electronic systems. Prerequisites: EE 3300 or EE 3400 with a grade of "C" or better. Corequisite: EE 3150 with a grade of "C" or better.

EE 3355. Solid State Devices.

This course examines the physical principles and operational characteristics of semiconductor materials and electronic devices. Students analyze the mechanics of carrier motion, including drift, diffusion, and recombination processes within crystalline structures. Inquiry focuses on the development of physical and mathematical models for p-n junction diodes and their application in rectification and signal modulation. Students examine the internal physics and terminal behaviors of bipolar junction transistors and field-effect transistors to evaluate their roles as switches and amplifiers. Analysis includes the investigation of metal-oxide-semiconductor structures and their integration into complex microelectronic circuits. Students investigate the impact of doping concentrations, temperature variations, and geometric scaling on device performance and reliability. Discussions evaluate the transition from discrete-component physics to the architectural constraints of integrated-circuit fabrication. Systematic inquiry into solid-state theory provides a framework for the development of modern microelectronic technologies. Prerequisite: [EE 3300 or EE3400] and PHYS 2326 with grades of "C" or better.

EE 3370. Signals and Systems.

This course examines the mathematical representation of signals and systems in both time and frequency domains. Students analyze the properties of linear time-invariant systems using convolution and differential equations to evaluate system stability. Inquiry focuses on the application of Fourier series and Fourier transforms to characterize periodic and aperiodic signals. Students examine the role of Laplace transforms in circuit analysis and the derivation of transfer functions for system design. Analysis includes the study of z-transforms and sampling theory to evaluate the transition to discrete-time processing. Students investigate frequency response characteristics and filter design to determine signal modification through various network architectures. Evaluation of these transformation techniques provides a framework for analyzing communication and control systems. Systematic inquiry into signal processing identifies the fundamental limits of information transmission and system performance. Prerequisite: EE 3300 or EE3400 with a grade of "C" or better.

EE 4152. Introduction to VLSI Design Lab.

This course examines the implementation of Very Large Scale Integration (VLSI) systems through the application of computer-aided design (CAD) tools and verification methodologies. Students analyze the physical design flow of Complementary Metal-Oxide-Semiconductor (CMOS) integrated circuits, including schematic capture, layout generation, and parasitic extraction. Inquiry focuses on the verification of circuit functionality through design rule checks, layout-versus-schematic comparisons, and timing simulations. Students examine the impact of physical constraints such as area, power, and delay on the performance of complex digital architectures. Analysis includes the optimization of cell-based designs and the synthesis of hardware descriptions into physical realizations. Students investigate the relationship between semiconductor fabrication limits and design rule specifications. Discussions evaluate the transition from high-level logic representations to silicon-level physical layouts. Systematic evaluation of these design processes provides a framework for the development of high-performance microelectronic systems. Prerequisite: EE 3350 and [CS 2420 or EE 2320] with grades of "C" or better. Corequisite: EE 4252 with grade of "C" or better.

EE 4155. Analog and Mixed-Signal Lab.

This course examines the design and verification of analog and mixed-signal circuits through the implementation of integrated system architectures. Students analyze the performance of operational amplifiers, comparators, and voltage references within complex feedback networks. Inquiry focuses on the characterization of data converters, specifically analog-to-digital and digital-to-analog interfaces, to evaluate resolution and sampling rates. Students examine the impact of noise, supply variations, and parasitic elements on signal integrity and dynamic range. Analysis includes the implementation of layout techniques and the use of simulation tools to verify circuit functionality against physical specifications. Students investigate the relationship between discrete-time and continuous-time signals within hybrid electronic environments. Evaluation of these mixed-signal structures identifies the fundamental limits of precision and speed in modern electronic systems. Systematic inquiry into integrated design processes provides a framework for the development of high-performance communication and sensor platforms. Prerequisite: EE 3370 and [EE 4350 or [EE 3350 and EE 3150]] with grades of "C" or better. Corequisite: EE 4255 with a grade of "C" or better.

EE 4180. Electric Machines Lab.

This course examines the principles of electromechanical energy conversion through the study of magnetic circuits and rotating machines. Students analyze the operational characteristics of transformers, direct current machines, and induction motors to evaluate performance parameters such as torque, speed, and efficiency. Inquiry focuses on the implementation of equivalent circuit models and the synchronization of three-phase systems within electrical networks. Students examine the behavior of synchronous machines under varying load conditions and excitation levels to determine stability. Analysis includes the study of magnetic saturation, winding configurations, and power flow within industrial drive systems. Students investigate the impact of control strategies on motor dynamics and the conversion of electrical energy into mechanical work. Evaluation of these electromagnetic devices identifies the functional limits of energy distribution and mechanical actuation. Systematic inquiry into machine theory provides a framework for the development of sustainable power and propulsion systems. Prerequisite: EE 3340 with a grade of "C" or better. Corequisite: EE 4380 with a grade of "C" or better.

EE 4192. Microelectronics Manufacturing Laboratory.

This course examines the principles and methodologies of semiconductor fabrication through the study of unit processes and metrology. Students analyze metrology data, including film thickness and sheet resistance, to evaluate the consistency of thermal oxidation and diffusion. Inquiry focuses on the impact of photolithography parameters such as exposure duration and development time on critical dimension control and pattern resolution. Students examine etch selectivity and anisotropy by investigating the results of wet and dry etching modules on multilayer semiconductor structures. Analysis includes the design of fabrication process flows for microelectronic devices such as metal-oxide-semiconductor capacitors and junction diodes. Students investigate the impact of cleanroom protocols and environmental contamination on device yield and functional reliability through statistical methods. Evaluation of experimental results supports the formulation of optimized process recipes to address non-uniformity and structural defects. Systematic inquiry into manufacturing cycles identifies the relationship between process parameters and device performance. Prerequisite: [CHEM 1341 or CHEM 1335] with a grade of "C" or better. Corequisite: EE 4392 with a grade of "C" or better.

EE 4252. Introduction to Very Large Scale Design (VLSD).

This course examines the analysis and design of Complementary Metal-Oxide-Semiconductor (CMOS) integrated circuits through the study of transistor-level architectures and physical layout. Students analyze the electrical characteristics of MOSFET devices, including switching behavior, power dissipation, and propagation delay. Inquiry focuses on the implementation of static and dynamic logic families and the design of complex arithmetic units such as adders and multipliers. Students examine the hierarchical design flow, from schematic capture to physical verification and timing analysis. Analysis includes the investigation of semiconductor fabrication constraints, design rule specifications, and the optimization of area-power-delay tradeoffs. Students investigate the architecture of memory arrays and the integration of digital systems within Very Large Scale Integration (VLSI) frameworks. Evaluation of these microelectronic structures identifies the relationship between circuit topology and system performance. Systematic inquiry into silicon-level design provides a framework for the development of high-density electronic processors. Prerequisite: EE 3350 and [CS 2420 or EE 2320] with grades of "C" or better. Corequisite: EE 4152 with grade of "C" or better.

EE 4255. Analog and Mixed-Signal Design.

This course examines the design and application of operational amplifiers, focusing on feedback topologies, offset voltage, and frequency stability. Students analyze compensation techniques to evaluate system performance and maintain closed-loop stability across varying operating conditions. Inquiry focuses on the characterization of random signals and the impact of noise on precision analog architectures. Students examine the operation of discrete-time circuitry and the fundamental principles of sampled-data systems. Analysis includes the architecture of data converters, specifically the conversion of signals between continuous and discrete domains using analog-to-digital and digital-to-analog interfaces. Students investigate the relationship between sampling rates, quantization error, and dynamic range within mixed-signal frameworks. Evaluation of these hybrid electronic structures identifies the fundamental limits of signal processing accuracy. Systematic inquiry into integrated design processes provides a framework for the development of high-performance communication and sensor platforms. Prerequisite: EE 3370 and [EE 4350 or [EE 3350 and EE 3150]] with grades of C or better. Corequisite: EE 4155 with a grade of "C" or better.

EE 4290. Electrical Engineering Design I.

This course examines the integration of engineering principles through the collaborative design of electrical systems or components. Students analyze industry-standard design processes to facilitate the conceptualization, implementation, and verification of technical projects. Inquiry focuses on the systematic documentation of project definitions, design trade-offs, and implementation specifications. Students examine the relationship between theoretical constraints and physical realization within a team-based environment. Analysis includes the evaluation of project performance against predefined criteria and the synthesis of complex data for technical communication. Students investigate methodologies for effective project management, risk assessment, and resource allocation. Discussions evaluate the impact of design decisions on system reliability and functional outcomes. Professional inquiry into these collaborative processes provides a framework for the execution of complex engineering tasks. Prerequisite: EE 3320 and EE 3120 and EE 3350 and EE 3370 and IE 3320 with grades of "C" or better. Corequisite: EE 4252 or EE 4356 or EE 4360 or EE 4370 with a grade of "C" or better.

EE 4291. Electrical Engineering Design II.

This course examines the advanced phases of the engineering design cycle, focusing on the rigorous implementation and verification of complex electrical systems. Students analyze experimental results and performance metrics to validate project specifications and functional reliability. Inquiry focuses on the iterative refinement of design prototypes through systematic testing and troubleshooting. Students examine the impact of physical constraints, component tolerances, and environmental factors on final system performance. Analysis includes the comprehensive documentation of design decisions, implementation details, and verification procedures within a professional engineering framework. Students investigate the relationship between theoretical modeling and realized hardware or software performance. Discussions evaluate the transition from initial conceptualization to a fully functional engineering solution. Systematic inquiry into these validation processes provides a framework for the successful execution of industry-standard technical projects. Prerequisite: EE 4290 with a grade of "C" or better. Corequisite: EE 4252 or EE 4370 with a grade of "C" or better.

EE 4321. Digital Systems Design Using HDL.

This course examines the design and implementation of digital systems using hardware description languages (HDL) to realize complex logic architectures. Students analyze register-transfer level (RTL) modeling techniques to evaluate the performance and efficiency of digital circuits. Inquiry focuses on the development of custom microprocessor cores and the integration of peripheral control units within programmable logic environments. Students examine the synthesis process and the mapping of HDL code to physical hardware resources such as field-programmable gate arrays. Analysis includes timing verification, functional simulation, and the optimization of area-power-delay characteristics for high-speed digital systems. Students investigate the design of finite state machines and memory hierarchies to support advanced computational tasks. Evaluation of these architectural frameworks identifies the transition from high-level behavioral descriptions to hardware-specific implementations. Systematic inquiry into digital design methodologies provides a framework for the development of modern integrated processing platforms. Prerequisite: [EE 3320 or EE 3420] with a grade of "C" or better.

EE 4323. Digital Image Processing.

This course examines the fundamental principles and methodologies of digital image processing and computer vision. Students analyze digital image representation, sampling, and quantization to evaluate data integrity within visual systems. Inquiry focuses on the application of spatial and frequency domain filtering techniques for image enhancement and restoration. Students examine the behavior of image segmentation algorithms and feature extraction processes for object recognition. Analysis includes the study of image compression standards, morphological operations, and color image processing within diverse technical frameworks. Students investigate the impact of noise and distortion on automated visual analysis and system reliability. Evaluation of these computational techniques identifies the relationship between pixel-level manipulation and high-level scene interpretation. Systematic inquiry into digital processing supports the development of robust visual perception systems. Prerequisite: EE 3370 and [EE 3320 or EE 3420] with grades of "C" or better.

EE 4331. Introduction to Machine Learning for Engineering Applications.

This course examines the fundamental principles of machine learning with a focus on deep learning architectures for engineering applications. Students analyze model characteristics and neural network theory to evaluate system performance and learning efficiency. Inquiry focuses on the implementation of classifiers for signal processing and network optimization tasks. Students examine regression models and convolutional neural networks for object detection and visual data analysis. Analysis includes the study of time-series forecasting and the integration of predictive modeling within smart city frameworks. Students investigate the relationship between dataset quality, hyperparameter tuning, and algorithm reliability. Discussions evaluate the transition from theoretical mathematical models to functional implementations in technical environments. Systematic inquiry into these computational tools provides a framework for the development of intelligent engineering systems. Prerequisite: CS 1428 or CS 1342 with a grade of "C" or better.

EE 4332. Introduction to Computer-Aided Engineering (CAE) Simulation on High-Performance Computing (HPC) Syst.

This course examines the development of engineering simulations optimized for high-performance computing environments. Students analyze programming techniques for multicore processors and the architectural constraints of memory systems. Inquiry focuses on the implementation of algorithms for dense and sparse linear algebra applications within parallel frameworks. Students examine computational models for thermal analysis, fluid dynamics, and stencil operations to evaluate system behavior. Analysis includes the application of stochastic algorithms and other numerical methods to complex engineering problems. Students investigate the relationship between hardware architecture and computational efficiency in large-scale simulation. Evaluation of these high-performance strategies identifies the fundamental limits of speed and scalability in technical computing. Systematic inquiry into parallel architectures provides a framework for the design of robust simulation tools for various engineering disciplines. Prerequisite: CS 1428 with a grade of "C" or better.

EE 4351. Fundamentals of Electroceramics.

This course examines the principles of electroceramic materials, focusing on the relationship between crystal structure and macroscopic electrical properties. Students analyze binary and ternary phase diagrams to evaluate material stability and phase transitions within complex oxide systems. Inquiry focuses on the symmetry groups and non-centro-symmetric crystal structures that govern nonlinear dielectric behaviors, including ferroelectricity, piezoelectricity, and pyroelectricity. Students examine the application of nonlinear magnetics and wideband gap semiconductors in the design of advanced detectors and sensors. Analysis includes the investigation of radiation-hardened electronics, spintronics technology, and the integration of micro-electro-mechanical systems (MEMS). Students investigate methodologies for materials processing, characterization, and fabrication to determine the physical constraints of device performance. Discussions evaluate the impact of structural defects and grain boundaries on the functional reliability of ceramic components. Systematic inquiry into electroceramic theory provides a framework for the development of high-performance electronic and magnetic platforms. Prerequisite: ENGR 2300 with a grade of "C" or better and a minimum 2.25 Overall GPA. Corequisite: EE 3355 with a grade of "C" or better.

EE 4353. Fundamentals of Advanced Semiconductor Technology.

This course examines the fundamental principles of advanced semiconductor technology and the evolution of integrated circuit scaling beyond Moore’s Law. Students analyze the physical limits of MOSFET and CMOS architectures and the impact of geometric scaling on device performance. Inquiry focuses on the implementation of high-K gate dielectrics and the integration of new channel materials to replace traditional silicon substrates. Students examine three-dimensional device structures, such as FinFETs and gate-all-around architectures, to evaluate electrostatic control and leakage current. Analysis includes the operation of compound semiconductor devices, specifically MESFETs and high-electron-mobility transistors (HEMTs), for high-frequency applications. Students investigate the physics of optoelectronic components, including light-emitting diodes, lasers, and solar cells, within various material systems. Evaluation of these emerging technologies identifies the relationship between material properties and functional device characteristics. Systematic inquiry into advanced fabrication techniques provides a framework for the development of next-generation microelectronic and photonic systems. Prerequisite: EE 3355 with a grade of "C" or better.

EE 4354. Flexible Electronics.

This course examines the materials systems, fabrication processes, and device physics of flexible electronic architectures. Students analyze the properties of semiconductor materials, including amorphous silicon, nanocrystalline silicon, and organic or polymeric substrates. Inquiry focuses on the application of solution-cast films, such as carbon nanotubes, and their role in achieving mechanical flexibility. Students examine the operational principles of high-speed transistors, thin-film photovoltaics, and flexible flat-panel displays. Analysis includes the study of medical image sensors and other integrated flexible systems to evaluate performance under mechanical strain. Students investigate the relationship between material deposition techniques and the functional reliability of conformable electronic devices. Evaluation of these emerging technologies identifies the technical challenges of integrating non-rigid components into modern electronic platforms. Systematic inquiry into flexible electronics provides a framework for the development of next-generation wearable and portable technologies. Prerequisite: EE 3350 and EE 3355 and EE 4350 with grades of "C" or better.

EE 4356. Power Electronics.

This course examines the principles of power electronics and the application of semiconductor circuits for the efficient control and conversion of electrical energy. Students analyze the operational characteristics and switching behaviors of power semiconductor devices, including diodes, thyristors, and transistors. Inquiry focuses on the design and implementation of DC-DC converters and multilevel converter architectures to evaluate voltage regulation and power density. Students examine the theory of power inverters and AC voltage controllers to determine the conversion of energy between direct and alternating current systems. Analysis includes the investigation of pulse-width modulation and harmonic distortion to evaluate signal quality and efficiency. Students investigate the relationship between thermal management, electromagnetic interference, and the reliability of high-power electronic systems. Evaluation of these conversion topologies identifies the fundamental limits of energy efficiency in industrial and renewable applications. Systematic inquiry into power electronic theory provides a framework for the development of modern energy systems. Prerequisite: [EE 4350 or [EE 3350 and EE 3150]] with a grade of "C" or better.

EE 4357. Introduction to Power Systems.

This course examines the fundamental principles of electrical power systems and the analysis of grid-level energy distribution. Students analyze the operational characteristics of power generation units and the mechanics of transformer action within interconnected networks. Inquiry focuses on transmission line modeling and the application of symmetrical components to evaluate system behavior under various loading conditions. Students examine real and quadrature power calculations alongside methodologies for power factor correction to optimize energy efficiency. Analysis includes the implementation of load flow algorithms to determine voltage profiles and power distribution across complex bus architectures. Students investigate economic considerations in system operations, including dispatch strategies and the management of generation resources. Evaluation of these power system elements identifies the technical constraints of maintaining grid stability and reliability. Systematic inquiry into power engineering provides a framework for the development of sustainable energy infrastructures. Prerequisite: EE 3300 or EE 3400 or ENGR 3373 with a grade of "C" or better.

EE 4359. Advanced Electronic Materials and Devices.

This course examines the principles of modern fabrication techniques and the properties of conventional and emerging electronic materials. Students analyze thin film deposition methodologies and advanced manufacturing concepts to evaluate material growth and structural integrity. Inquiry focuses on the role of heterointerfaces and the characterization of electronic, thermal, magnetic, and optical properties within solid-state systems. Students examine the operational physics of practical devices, including photovoltaic cells, light-emitting diodes, and high-resolution display technologies. Analysis includes the investigation of emerging flexible electronic platforms and the challenges of integrating non-rigid materials into functional architectures. Students investigate the relationship between material morphology and the resulting performance of optoelectronic and microelectronic components. Discussions evaluate the transition from fundamental material science to the realization of high-performance technical devices. Systematic inquiry into electronic materials provides a framework for the development of next-generation solid-state and flexible technologies. Prerequisite: EE 3350 with a grade "C" or better.

EE 4360. Linear Control Systems.

This course examines the principles of linear continuous-time and discrete-time automatic control systems through the application of mathematical modeling and feedback theory. Students analyze system dynamics in both time and frequency domains to evaluate the performance of closed-loop architectures. Inquiry focuses on the implementation of transfer function representations and state variable analysis for system characterization. Students examine transient and steady-state responses to determine the impact of damping, natural frequency, and error constants on precision. Analysis includes the study of stability criteria, such as the Routh-Hurwitz and Nyquist methods, alongside sensitivity analysis to evaluate robustness against parameter variations. Students investigate the design of compensators and controllers to achieve desired system behaviors. Evaluation of these control strategies identifies the fundamental limits of regulation and tracking in technical environments. Systematic inquiry into linear systems provides a framework for the development of automated and autonomous technologies. Prerequisite: EE 3370 and MATH 3376 with grades of "C" or better.

EE 4370. Communication Systems.

This course examines the transmission of signals through linear systems and the fundamental principles of communication theory. Students analyze analog and digital modulation techniques, including amplitude, frequency, and phase-shift keying, to evaluate bandwidth efficiency and signal integrity. Inquiry focuses on the characterization of noise and its impact on information recovery within stochastic environments. Students examine the design of optimal filters and synchronization methods to determine the limits of data transmission over diverse channels. Analysis includes the investigation of signal-to-noise ratios and bit error rates to evaluate system performance. Students investigate the relationship between sampling theory, quantization, and the reconstruction of continuous-time signals. Evaluation of these modulation frameworks identifies the technical trade-offs between power, bandwidth, and complexity. Systematic inquiry into communication architectures provides a framework for the development of modern wireless and wired networks. Prerequisites: EE 3370 and IE 3320 with grades of "C" or better.

EE 4372. Communication Networks.

This course examines the architecture and functional principles of modern data communication systems through the study of networked environments. Students analyze the 7-layer OSI model to evaluate how protocols and algorithms facilitate seamless information exchange across diverse platforms. Inquiry focuses on the physical media and local area network (LAN) components that define the hardware constraints of signal transmission. Students examine the implementation of Ethernet and TCP/IP suites as the foundational standards for global connectivity and reliable data routing. Analysis includes the investigation of network topologies and the performance metrics of various communication standards. Students investigate the relationship between layered architectures and the security, scalability, and efficiency of interconnected systems. Evaluation of these networking frameworks identifies the technical challenges of managing high-speed data traffic. Systematic inquiry into communication protocols provides a framework for the development of robust and interoperable information networks. Prerequisite: EE 3320 or EE 3420 with a grade of "C" or better. Corequisite: EE 3370 with a grade of "C" or better.

EE 4374. Introduction to Wireless Communication.

This course examines the fundamental principles and operational architectures of modern wireless communication systems. Students analyze the mechanics of signal modulation and demodulation to evaluate spectral efficiency and information integrity across mobile channels. Inquiry focuses on the implementation of source and channel coding techniques to ensure robust data transmission in the presence of interference and noise. Students examine multiple access methodologies, including frequency, time, and code division protocols, to determine how network resources are shared among multiple users. Analysis includes the investigation of radio frequency propagation models and the physical constraints of cellular environments. Students investigate the relationship between link budgets, fading phenomena, and system capacity. Evaluation of these mobile technologies identifies the technical trade-offs between coverage, power, and data rates. Systematic inquiry into wireless theory provides a framework for the development of next-generation telecommunication networks. Prerequisites: EE 4370 with a grade of "C" or better.

EE 4375. Building a Smart Grid Architecture.

This course examines the transition from traditional centralized power grid architectures to decentralized smart grid frameworks. Students analyze the structural differences between 20th-century unidirectional power systems and 21st-century multidirectional energy networks. Inquiry focuses on the implementation of two-way power and data flows to facilitate real-time monitoring, control, and management of electrical resources. Students examine the integration of traditional bulk generation with renewable and distributed energy resources to evaluate grid stability and reliability. Analysis includes the investigation of communication protocols and sensor technologies required for automated energy distribution. Students investigate the relationship between information infrastructure and the optimization of power consumption across diverse load profiles. Evaluation of these modernization strategies identifies the technical challenges of managing complex energy portfolios. Systematic inquiry into smart grid architectures provides a framework for the development of sustainable and resilient power infrastructures. Prerequisite: EE 3370 with a grade of "C" or better.

EE 4376. Introduction to Telecommunications.

This course examines the fundamental principles of telecommunications and the architectural evolution of global communication networks. Students analyze the operation of telephone networks and the mechanics of switching and transmission systems. Inquiry focuses on the differentiation between circuit-switched and packet-switched paradigms to evaluate data throughput, latency, and resource allocation. Students examine the processes of cell processing and the application of queuing theory to determine system capacity and congestion management within high-traffic environments. Analysis includes the investigation of signal propagation through diverse transmission media and the performance metrics of modern telecommunication links. Students investigate the relationship between network topology and the reliability of information exchange across distributed systems. Evaluation of these switching frameworks identifies the technical trade-offs between fixed-bandwidth and demand-based connectivity strategies. Systematic inquiry into telecommunication theory provides a framework for the development of modern voice and data infrastructures. Co-requisite: EE 4370 with a grade of "C" or better.

EE 4377. Introduction to Digital Signal Processing.

This course examines the fundamental principles of discrete-time signals and systems within the context of digital signal processing. Students analyze discrete systems, convolution, and spectral analysis to evaluate signal behavior in the digital domain. Inquiry focuses on the design and implementation of Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters. Students examine the Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) algorithms to determine frequency components and computational efficiency. Analysis includes the study of z-transforms, sampling theory, and the impact of quantization effects on system performance. Students investigate the relationship between windowing functions and spectral leakage in signal characterization. Evaluation of these processing techniques identifies the trade-offs between computational complexity, phase linearity, and filter response accuracy. Systematic inquiry into digital signal theory provides a framework for the development of modern audio, video, and communication processing platforms. Prerequisites: EE 3370 with a grade of "C" or better.

EE 4378. Data Compression and Error Control Coding.

This course examines the principles of information theory and the mathematical foundations of data representation and transmission. Students analyze the information content of messages and the concept of entropy to evaluate the limits of source coding and data compression. Inquiry focuses on the determination of channel capacity and the implementation of data translation codes to optimize communication efficiency. Students examine the fundamentals of error-correcting codes, including linear block and convolutional structures, to ensure signal integrity across noisy channels. Analysis includes the study of Huffman coding and Lempel-Ziv algorithms to determine optimal compression ratios. Students investigate the relationship between redundancy, bandwidth, and the probability of error in digital systems. Evaluation of these coding strategies identifies the technical trade-offs between data density and error recovery capabilities. Systematic inquiry into information theory provides a framework for the development of secure and efficient data storage and transmission platforms. Corequisite: EE 4370 with a grade of "C" or better.

EE 4380. Electric Machines.

This course examines the principles and analysis of electromechanical systems and the fundamental conversion of energy between electrical and mechanical domains. Students analyze electromagnetic field interactions and the mathematical laws governing motor and generator operations. Inquiry focuses on the development of analytical models to predict device performance and system interaction characteristics under varying load conditions. Students examine the operational physics of major classes of electric machines, including direct current, synchronous, and induction motors. Analysis includes the study of equivalent circuit models, magnetic flux distribution, and torque production within rotating machinery. Students investigate the relationship between power flow, efficiency, and the thermal constraints of magnetic materials. Evaluation of these electromechanical frameworks identifies the technical trade-offs between speed regulation, starting torque, and power density. Systematic inquiry into machine design provides a framework for the development of modern industrial drives and energy conversion systems. Prerequisite: EE 3340 with a grade of "C" or better.

EE 4381. Sustainable Energy & Storage.

This course examines the consumption and production of energy and the principles and technologies behind renewable energy sources. Students analyze the operational physics of solar, wind, and hydroelectric systems to evaluate power generation efficiency. Inquiry focuses on the integration of intermittent energy resources into the electrical grid and the impact on system stability. Students examine the mechanics of various energy storage technologies, including electrochemical batteries, gravitational systems, and hybrid configurations. Analysis includes the study of energy conversion processes, thermal constraints, and the lifecycle assessment of sustainable power architectures. Students investigate the relationship between energy demand profiles and the scalability of distributed generation. Evaluation of these renewable frameworks identifies the technical trade-offs between cost, environmental impact, and grid reliability. Systematic inquiry into energy systems provides a framework for the development of resilient and sustainable power infrastructures. Prerequisite: [EE 3300 or EE 3400] and PHYS 2326 and CHEM 1335 with grades of "C" or better.

EE 4382. Advanced Power Systems.

This course examines the advanced principles of power system analysis and the operational dynamics of interconnected electrical networks. Students analyze symmetrical and unsymmetrical faults to evaluate system response and protection requirements under abnormal conditions. Inquiry focuses on the application of symmetrical components to characterize unbalanced circuits and sequence networks. Students examine the functional principles of system protection, including relay coordination and circuit breaker operation. Analysis includes the investigation of transient stability and the power-angle relationship to determine grid resilience against sudden disturbances. Students investigate the transient behavior of transmission lines and the mechanics of surge propagation. Evaluation of supervisory control and data acquisition (SCADA) frameworks identifies the technical infrastructure required for real-time monitoring and automated system management. Systematic inquiry into power system dynamics provides a framework for the development of secure and stable energy infrastructures. Prerequisite: EE 4357 with a grade of "C" or better.

EE 4392. Microelectronics Manufacturing.

This course examines the principles of integrated circuit fabrication and the sequential processes of semiconductor manufacturing. Students analyze crystal growth and wafer preparation techniques to evaluate substrate quality and lattice integrity. Inquiry focuses on epitaxial growth, thermal oxidation, and diffusion processes as methods for altering material properties. Students examine the physics of ion implantation and thin-film deposition to determine dopant profiles and interconnect reliability. Analysis includes the study of photolithography and etching methodologies required for precise feature patterning at the microscale. Students investigate device and circuit formation alongside the technical constraints of packaging and electrical testing. Evaluation of these manufacturing stages identifies the relationship between process control and functional yield. Systematic inquiry into microelectronic fabrication provides a framework for the development of modern solid-state technologies. Prerequisite: CHEM 1341 or CHEM 1335 with a grade of "C" or better.

ENGR 1304. Engineering Graphics.

This course introduces the fundamental principles of engineering graphical communication through a blend of manual drawing and the use of CAD software. The scope encompasses the creation of precise two- and three-dimensional representations, focusing on the conventions of multiview projections, geometric relationships, and pictorials. Students engage in hands-on technical applications to produce working drawings using standard engineering conventions. The course emphasizes the translation of conceptual designs into standardized technical drawings used in industrial design and manufacturing contexts. Corequisite: MATH 2417 or MATH 2471 with a grade of "C" or better.

ENGR 2300. Materials Engineering.

This course introduces the structure, properties, processing, and performance of engineering materials, including metals, polymers, ceramics, and composites. The scope includes atomic bonding, crystal structures, phase diagrams, mechanical behavior, and electrical, magnetic, thermal, and optical properties, with emphasis on structure–property relationships in engineering applications. The course uses lectures, problem-solving sessions, and selected laboratory demonstrations to reinforce fundamental principles. The course emphasizes the application of materials science concepts to material selection and analysis of material behavior under various service conditions. Prerequisite: [CHEM 1335 and CHEM 1135] or [CHEM 1341 and CHEM 1141] with grades of "D" or better.

ENGR 2301. Statics.

This course covers the theory of engineering mechanics of stationary systems. Topics include the distinction between scalars and vectors, including force vectors, moment vectors, and couple moments acting on stationary structures; construction of free-body diagrams; and application of equations of equilibrium to particles and rigid bodies in two- and three-dimensional force systems. The course also addresses the analysis of simple truss and beam structures to determine internal forces such as axial force, shear force, and bending moment, as well as the calculation of centroids of composite bodies and cross-sections and moments of inertia about specified axes. Prerequisite: PHYS 2325 and 2125 with grades of "C" or better. Corequisite: MATH 2472 or MATH 2473 with a grade of "C" or better.

ENGR 2302. Dynamics.

This course introduces the fundamentals of kinematics and kinetics of individual particles, systems of particles, and rigid bodies. Topics include rectilinear motion, curvilinear motion, general plane motion, relative motion analysis, mass moment of inertia, Newton’s laws of motion, work and energy relationships, and the principles of impulse and momentum. Aspects related to the general three-dimensional motion of rigid bodies may also be considered. Emphasis is placed on application of kinetics and kinematics to the solution of engineering problems. Prerequisite: ENGR 2301 and MATH 2472 with grades of "C" or better.

ENGR 3190. Engineering Cooperative Education.

This course provides an academically supervised cooperative education (co‑op) experience in which students engage in paid, discipline‑related employment while concurrently enrolled in an associated academic course. Students plan, analyze, and evaluate their work experiences in relation to engineering concepts, professional practices, and workplace expectations. Emphasis is placed on applying classroom knowledge to professional projects and reflecting on technical and organizational processes encountered during employment. Prerequisite: Instructor Approval.

ENGR 3290. Advanced Engineering Cooperative Education.

This course provides an academically supervised cooperative education experience in which students engage in paid, discipline-related employment while concurrently enrolled in an associated academic course. Students plan, analyze, and evaluate their work experiences in relation to engineering concepts, professional practices, and workplace expectations. Emphasis is placed on applying classroom knowledge to professional projects and reflecting on technical and organizational processes encountered during employment. Prerequisite: Instructor Approval.

ENGR 3311. Mechanics of Materials.

This course examines the fundamental principles of mechanics of materials as applied to structural and mechanical components. The scope includes stress and strain, elastic modulus, Poisson’s ratio, constitutive equations, axial loading, torsion, bending, shear, bending moment diagrams, beam deflection, and column stability. Emphasis is placed on the relationship between loads, internal forces, stresses, and resulting deformations in engineering materials. The course is delivered through lectures and structured problem-solving sessions that develop analytical skills. The course emphasizes analysis and prediction of the mechanical response of structural members under various loading conditions. Prerequisite: ENGR 2301 with a grade of "D" or better.

ENGR 3315. Engineering Economic Analysis.

This course introduces principles and methods of engineering economic analysis for engineering and technology students. Topics include break-even analysis, interest and equivalence, learning curve and power sizing models, present worth, equivalent annual worth, rate of return, depreciation, and after-tax cash flow analysis. Students apply these methods to evaluate and compare engineering alternatives of moderate scope. Analytical techniques are implemented using both traditional compound interest tables and contemporary computer-based tools such as spreadsheet software. Emphasis is placed on systematic evaluation of costs, benefits, and timing of cash flows to support informed engineering decision making in professional practice. Prerequisite: MATH 1315 or MATH 2417 or MATH 2471 with a grade of "D" or better.

ENGR 3373. Circuits and Devices.

This course examines principles of electrical circuit analysis and the operational characteristics of electronic devices in engineering systems. Topics include fundamental circuit laws, network theorems, and analysis of DC and AC circuits. The course introduces electronic components such as diodes, transistors, and operational amplifiers and their application in signal processing and power management. Students examine the integration of sensors, transducers, and electromechanical devices in system design. Emphasis is placed on analyzing circuit behavior, evaluating system performance, and understanding relationships between circuit topology, signal integrity, and power efficiency in engineering applications. Prerequisite: PHYS 2326 and PHYS 2126 and [CS 1428 or CS 1342] with grades of "D" or better.

ENGR 3380. Fluid Mechanics.

This course examines the fundamental principles of fluid mechanics, including fluid statics, kinematics, and dynamics. Students analyze fluid motion through the application of conservation laws for mass, energy, and momentum. Dimensional analysis and similarity principles are explored to characterize physical processes. The course also addresses the use of sensing technologies for monitoring fluid flow and pressure. Laboratory exercises engage students in standardized experimental procedures, data acquisition, and analysis of measured results. Applications to civil engineering infrastructure, including forces on hydraulic structures and pipe flow analysis, are examined throughout the course. Prerequisite: ENGR 2301 and MATH 3323 with grades of "C" or better.

ENGR 4299. Engineering Undergraduate Research.

This course provides undergraduate students with an opportunity to conduct independent research on an approved engineering topic under faculty supervision. Students develop a research question, review relevant technical literature, design and implement appropriate experimental or investigative methods, analyze collected data, and communicate results using professional written and oral formats. Research is conducted individually with structured guidance to support methodological rigor, documentation quality, and adherence to established engineering research standards. The course emphasizes technical inquiry, analytical reasoning, and professional communication while allowing students to explore advanced engineering topics relevant to their academic and career interests. Prerequisite: Instructor approval.

ENGR 4395. Independent Studies in Engineering.

This course provides students with the opportunity to pursue a self-selected program of study under faculty supervision. Topics are flexible and may include emerging technologies, interdisciplinary applications, or advanced material such as participation in a graduate-level course. Students develop and execute a structured learning plan, integrating prior knowledge with new concepts to address complex engineering questions or projects. Emphasis is placed on independent inquiry, critical thinking, and professional communication. Deliverables typically include written reports, presentations, or project outcomes, demonstrating depth of understanding, technical competence, and the ability to apply engineering principles in a specialized area of interest. Prerequisite: Instructor approval.

IE 1310. Introduction to Industrial Engineering.

This course provides an introduction to the field of industrial engineering through examination of its historical development, foundational concepts, and principal areas of practice. Students are introduced to analytical methods and problem solving approaches used to analyze and design systems involving people, materials, information, and technology. Topics include productivity analysis, operations research, facilities planning, statistical process control, and human factors. The course also surveys career paths in manufacturing, healthcare, logistics, and service industries, emphasizing the professional roles and functions of industrial engineers within contemporary organizations. Prerequisite: [MATH 1315 or MATH 1317 or MATH 1319 or MATH 1329 or MATH 2321 or MATH 2417 or MATH 2471 with a grade of "C" or better] or [ACT Mathematics score of 24 or better] or [SAT Mathematics score of 520 or better] or [SAT Math Section score of 550 or better] or [Accuplacer College Mathematics score of 86 or better] or [Compass College Algebra score of 46 or better] or [Next-Generation Advanced Algebra and Functions Test of 263 or better].

IE 3305. Introduction to Data Analysis.

This course introduces principles and applications of data analysis using spreadsheet and programming tools, including Microsoft Excel, Python, and SQL. Students study methods for data manipulation, visualization, optimization, and decision support modeling within industrial engineering contexts. The course examines spreadsheet based productivity techniques, database interaction, and the use of programming languages for advanced analytical tasks. Students also explore contemporary machine learning methods as analytical tools used in modern industrial systems. Emphasis is placed on interpreting empirical data, constructing analytical models, and supporting technical decision making through systematic computational approaches. Corequisite: IE 3320 with a grade of "D" or better.

IE 3320. Engineering Statistics.

This course introduces principles of probability and statistics used in engineering analysis, including probability distributions, data visualization, interval estimation, hypothesis testing, and regression modeling. Students study statistical methods applied to engineering problems and contemporary data analysis contexts. The course examines mathematical frameworks for interpreting datasets, assessing variability, and evaluating statistical significance. Emphasis is placed on the use of descriptive and predictive statistical models to support technical analysis and informed engineering decision‑making. Prerequisites: MATH 2472 or MATH 2473 with a grade of "D" or better.

IE 3330. Quality Engineering.

This course provides an introduction to quality engineering methods used to analyze, monitor, and improve manufacturing and service processes. Students examine statistical tools for measuring process variability and apply continuous improvement methodologies to evaluate system performance. Topics include DMAIC, statistical process control, process capability analysis, and acceptance sampling. Emphasis is placed on data driven decision making and the use of statistical software to analyze quality characteristics. Through applied examples, students develop the ability to interpret results, assess process performance, and support engineering judgments in quality related contexts across diverse operational environments. Prerequisite: IE 3320 with a grade of "D" or better.

IE 3340. Operations Research.

This course examines fundamental optimization models and analytical methods in operations research, including linear programming, simplex-based algorithms, duality theory, sensitivity analysis, integer programming, and network flow models. Emphasis is placed on mathematical formulation, algorithmic solution techniques, and interpretation of model outcomes in engineering decision-making contexts. Students engage in quantitative modeling and computational implementation of optimization methods to address structured industrial problems. By the end of the course, students will be able to formulate optimization models, apply appropriate solution methods, analyze solution properties, and evaluate their practical implications. Prerequisite: [CS 1428 or CS 1342] and ENGR 3315 and MATH 3377 and IE 1310 with grades of "D" or better.

IE 3360. Lean Systems and Ergonomics.

This course examines lean process improvement tools, ergonomics, and work design principles used in industrial and service systems. Topics include time study and motion analysis, process mapping, 5S, line balancing, setup time reduction, standardized work, and work sampling. The course also introduces anthropometry and ergonomic design guidelines as analytical frameworks for evaluating human–system interaction. Emphasis is placed on applying quantitative and observational methods to analyze system performance, workplace design, and operational efficiency across manufacturing and service contexts. Prerequisite: IE 3320 with a grade of "D" or better.

IE 4310. Statistical Design of Experiments.

This course examines principles and analytical methods in the statistical design and analysis of experiments. Topics include hypothesis testing, analysis of variance, blocked and factorial designs, fractional factorial experiments, regression modeling, and response surface methodology. Emphasis is placed on experimental planning, model formulation, statistical inference, and interpretation of experimental results in engineering contexts. Students apply statistical modeling techniques and computational tools to analyze experimental data and evaluate system performance. By the end of the course, students will be able to design controlled experiments, analyze experimental data, and assess the validity and practical implications of statistical conclusions. Prerequisite: IE 3320 with a grade of "D" or better.

IE 4320. Integrated Production Systems.

This course introduces concepts and mathematical models used in the design and control of integrated production systems within manufacturing and service environments, emphasizing forecasting, aggregate production planning, inventory management, material requirements planning, and shop floor control. Students apply quantitative models and decision making tools to create demand forecasts, production plans, determine optimal inventory levels and reorder points, and schedule shop floor activities. Emphasis is placed on formulating engineering solutions, analyzing data to support operational decisions, and evaluating system performance. Prerequisite: IE 3320 with a grade of "D" or better. Corequisite: IE 3340 with a grade of "D" or better.

IE 4330. Reliability Engineering.

This course teaches analytical methods to model, design, and maintain system reliability, aiming to prevent and ensure equipment performance over its lifecycle. Key topics include statistical models such as exponential and Weibull lifetime distribution for components and systems, reliability block diagram for series, parallel, k-out-of-n redundancy and networks, accelerated life testing and proportional hazard rate model, failure in time and design for reliability, preventive and predictive maintenance, spare parts logistics and repairable inventory, and Markov decision process with applications in condition-based maintenance. Prerequisite: IE 3320 with a grade of "D" or better.

IE 4335. Lean Six Sigma Methodologies.

This course examines the principles and methodologies associated with Lean Six Sigma in manufacturing and service systems. Inquiry centers on structured improvement models such as DMAIC and PDCA and supporting tools for process analysis and control. Quantitative topics include statistical process control, introductory experimental design, and process risk assessment techniques used to evaluate process changes. The course examines approaches for diagnosing process issues, proposing improvements, and developing sustainment plans. Examples are drawn from both manufacturing and service enterprises. Prerequisite: IE 3330 and IE 4310 with grades of "D" or better.

IE 4340. Non-Linear Optimization Techniques.

This course introduces mathematical modeling and computational methods for nonlinear programming problems in engineering applications. The course presents techniques for optimizing unconstrained and constrained nonlinear models. Instructional methodology includes lectures and hands-on computational experiences using Python and multiple contemporary nonlinear optimization software. Students examine how problem structure affects tractability and solution quality. By the end of the course, students should be able to formulate and solve engineering problems using nonlinear programming approaches and evaluate solution performance in applied contexts. Prerequisite: IE 3340 with a grade of "D" or better.

IE 4342. Advanced Linear and Integer Programming.

This course examines advanced mathematical modeling and computational techniques used to formulate and solve linear and integer programming problems in engineering contexts. Students explore stochastic programming, dynamic programming, and decomposition methods that support large‑scale optimization. Emphasis is placed on understanding model structures, evaluating algorithmic approaches, and interpreting solution properties. Applications include manufacturing, service operations, supply chains, healthcare, and electrical systems. The course provides students with the analytical tools needed to select appropriate models, apply solution algorithms, and assess computational performance in complex decision‑making environments. Prerequisite: IE 3340 with a grade of “D” or better.

IE 4350. Supply-Chain Engineering.

This course examines engineering and managerial issues in supply chain systems with an emphasis on decision making in complex operational environments. Topics include supply chain strategy, network design, demand and supply planning, inventory management, sourcing, transportation, pricing, and coordination enabled by information systems. The course emphasizes how decisions across multiple stages of a supply chain interact and influence overall system performance. Through analytical modeling and problem solving, students evaluate tradeoffs among cost, service level, responsiveness, and operational efficiency in manufacturing and service settings. Prerequisite: IE 3340 with a grade of "D" or better.

IE 4355. Facilities Planning.

This course examines principles and analytical methods for facility planning, layout design, and material handling systems. Topics include facility location, plant layout models, space requirements analysis, warehouse operations, material handling equipment selection, and system integration considerations. Emphasis is placed on quantitative modeling, systematic layout design procedures, and evaluation of alternative facility configurations under operational constraints. Students apply analytical tools and design methodologies to develop and assess facility planning solutions for manufacturing and service environments. By the end of the course, students will be able to analyze facility systems, design layout alternatives, and evaluate operational performance implications. Prerequisite: ENGR 3315 and MFGE 2332 with grades of "D" or better.

IE 4360. Human Factors Design.

This course introduces principles and practices of human factors engineering applied to the design and development of ergonomic systems and products. Students apply anthropometric and human performance data using experimental and observational methods to evaluate engineering designs. Emphasis is placed on integrating human capabilities and limitations into engineering decision‑making within technical and safety constraints. Through projects and case studies, students examine the application of human factors methods across multiple engineering contexts and assess their impact on system performance, safety, and usability. Prerequisites: IE 3360 with a grade of "D" or better.

IE 4370. Probabilistic Operations Research.

This course describes probabilistic models in operations research to include queuing theory, simulation, and Markov chains. Main topics include discrete Markov transition models and probability matrix, Ergodic and non-ergodic Markov process, computing steady-state probability using one-step transition probability, death-birth queueing model, Little’s law, Erlang B and Erlang C queueing systems, and machine repairperson problem. Emphasis will be placed on modeling applications to solve problems in manufacturing and service industry sectors, such as aerospace, energy production, retail stores and maintenance logistics supply chains. Prerequisite: [CS 1428 or CS 1342] and IE 3320 with grades of "D" or better.

IE 4381. Introduction to Systems Engineering.

This course explores the strategic design and management of complex, large-scale systems and their interdependencies within a "systems of systems" framework. The scope encompasses the entire lifecycle, from initial needs analysis and concept definition to final integration and evaluation. Students will apply systems thinking methodologies to model and solve multi-disciplinary engineering challenges. Upon completion, participants will be equipped to lead technical projects using standardized systems engineering processes to ensure operational efficiency and resilience. Prerequisite: IE 3320 with a grade of "D" or better.

IE 4392. Industrial Engineering Design I.

This course introduces students to the application of Industrial Engineering principles in a project‑based, team‑oriented environment. Students analyze industrial and systems engineering problems, identify technical and economic constraints, and apply relevant engineering standards under realistic conditions. Through structured planning, documentation, and iterative development, student teams learn to design, evaluate, and communicate engineering solutions for real or simulated industrial contexts. Emphasis is placed on effective project management, professional communication, and the ability to integrate knowledge acquired in prior engineering coursework. This course serves as the first part of a two‑course sequence and prepares students for continued project development in Industrial Engineering Design II (IE 4393). Prerequisite: IE 3330 and IE 3340 and IE 3360 all with grades of "D" or better. Corequisite: 6 hours from [IE 4310 or IE 4355 or IE 4370] both with grades of "D" or better.

IE 4393. Industrial Engineering Design II.

This course continues the two‑semester design sequence by guiding student teams through the implementation and evaluation of solutions to industrial and systems engineering problems. Students work within realistic technical, economic, and organizational constraints while applying analytical methods learned in previous coursework. Emphasis is placed on project definition, modeling, documentation, and adherence to relevant engineering standards. Teams prepare written reports and deliver oral presentations that communicate design decisions to diverse stakeholders. The course provides structured opportunities for applying professional skills in problem solving, documentation, and technical communication. Prerequisite: IE 4392 and 6 hours from [IE 4310 or IE 4355 or IE 4370] with grades of "D" or better. Corequisite: 6 hours from [IE 4320 or IE 4350 or MFGE 4396] with grades of "D" or better.

IE 4399D. Heuristic Optimization Techniques.

This course introduces heuristic and metaheuristic optimization methods for solving large scale and computationally challenging engineering problems. Topics include problem complexity, NP hardness, constructive and improvement heuristics, and major metaheuristic frameworks such as simulated annealing, tabu search, genetic algorithms, ant colony optimization, and particle swarm optimization. Applications are drawn from scheduling, routing, logistics, and resource allocation. Through algorithm development, computational implementation, and evaluation of solution performance, students learn to design, implement, and assess heuristic methods for optimization problems where exact approaches are computationally impractical. Prerequisite: [CS 1428 or CS 1342] and IE 3340 with grades of "D" or better.

IE 4399G. Special Topics in Project Management.

This course provides undergraduate students with solid foundations of project management. Classical, prescriptive and adaptive methodologies are presented. Students will get to know different standards in project management, whereas the main focus will be on those from PMI (Project Management Institute). This course covers all phases of project management and introduces the most relevant tools and techniques to initiate, plan and execute projects in different contexts successfully. In addition to techniques, the “soft” perspective of managing people and their cooperation within projects will be addressed in detail.

ME 1101. Introduction to Digital Mechanical Engineering Lab.

This course introduces students to foundational engineering principles, laboratory practices, and digital engineering technologies. Topics include basic data analysis, introductory microcontroller programming, the product design process, and emerging technologies such as additive manufacturing, artificial intelligence, and augmented reality. Students participate in hands-on laboratory activities, structured design challenges, and collaborative projects to apply core concepts in practical settings. By the end of the course, students will be able to demonstrate foundational engineering knowledge and apply basic digital tools, data analysis methods, and programming concepts to solve simple engineering problems. Corequisite: [MATH 2417 or MATH 2471] and ENGR 1304 and ME 1201 with grades of “C” or better.

ME 1201. Introduction to Digital Mechanical Engineering.

This course examines mechanical engineering as a discipline and a profession. Topics include the mechanical engineering profession, career pathways in mechanical engineering, engineering ethics, representation of technical information, the engineering approach for solving problems, application of mathematical and scientific principles to solve simple engineering problems, an introduction to the product design and development process, an introduction to basic systems thinking and systems engineering concepts, and a general overview of tools and technologies such as the Internet of things (IoT), sensors, computer simulations and digital twins, virtual and augmented reality, robotics and autonomous robots, additive manufacturing, big data and data analytics, artificial intelligence, and sensor security in mechanical systems. Corequisite: MATH 2417 or MATH 2471 with a grade of "C" or better.

ME 3112. Mechanical Behavior of Materials Lab.

This laboratory course examines experimental stress analysis techniques and standard mechanical tests used to characterize the behavior of engineering materials under different loading conditions. Students perform experiments, analyze data, and interpret results in relation to analytical predictions, material models, and sources of experimental uncertainty. The course emphasizes the comparison of measured material response with theoretical expectations and the evaluation of discrepancies between experiment and analysis. Laboratory topics include tension, compression, bending, torsion, and shear tests of both polymeric and metallic materials, along with hardness measurement, metallography, application of strain gauges, fatigue behavior of materials, creep and stress relaxation, photoelasticity, and digital image correlation. Students develop practical skills in materials testing, experimental methods, data interpretation, and assessment of relationships among material structure, loading, deformation, and failure. Prerequisite: ENGR 2300 with a grade of “C” or better. Corequisite: ME 3311 with a grade of "C" or better.

ME 3151. Smart Instrumentation and Measurement Lab.

This course introduces students to smart instrumentation and measurement systems used in modern mechanical engineering applications. Topics include fundamental measurement principles, analog and digital instrumentation, data acquisition (DAQ) systems, signal conditioning, and the application of sensors within engineering systems and Internet of Things (IoT) networks. Students engage in structured, hands-on laboratory experiments using wired and wireless digital communication and computer-based data acquisition tools. By the end of the course, students will develop the ability to effectively acquire, analyze, and evaluate measurement data for engineering decision-making. Prerequisite: ME 1101 and ENGR 3373 and ENGR 3311 and ME 3330 with grades of "C" or better. Corequisite: ME 3351 and IE 3320 with grades of “C” or better.

ME 3311. Mechanics of Solids.

This course covers advanced topics in solid mechanics, focusing on the behavior of deformable bodies under complex loading environments, including statically indeterminate problems. The scope extends to topics such as thermal stresses and inelastic deformations, while also addressing stress concentrations and failure criteria under static and cyclic loading. Utilizing analytical methodologies like Mohr’s circle and transformation equations, students evaluate principal stresses and planes and determine maximum shear stresses. Prerequisite: ENGR 3311 with a grade of "C" or better.

ME 3314. Machine Design.

This course applies knowledge of statics, dynamics, mechanics of solids, and engineering materials to the design and selection of machine elements. Topics include fatigue failure theories, material selection, impact loading, and typical machine elements such as transmission shafts, keys, bearings, gears, springs, and fasteners. The course emphasizes analytical methods and standard design procedures to evaluate component performance under various loading conditions. Upon completion, students should be able to analyze and design machine elements and assess their reliability and safety in engineering applications. Prerequisite: ENGR 2302 and ME 3311 with grades of "C" or better. Corequisite: ME 3112 with a grade of “C” or better.

ME 3330. Engineering Thermodynamics.

This course examines introductory concepts of thermodynamics including energy transfer and general energy analysis, properties of pure substances, the ideal gas model, and basic principles of the first and second laws of thermodynamics. Students develop a general energy balance applied to closed and open systems and apply the second law of thermodynamics to these systems. The course teaches idealized isentropic processes and problem solving that requires an understanding of conservation of energy, conservation of mass, and the second law of thermodynamics for open and closed systems, gas and steam power cycles, and refrigeration cycles. Prerequisite: [PHYS 2325 and PHYS 2125] and MATH 2472 with grades of "C" or better.

ME 3331. Heat Transfer.

This course introduces the fundamental concepts and governing equations of heat transfer, including steady-state and transient conduction in one- and two-dimensional systems, external and internal forced convection, natural convection, heat exchangers, and the fundamentals of thermal radiation. The scope emphasizes the formulation, modeling, and analysis of thermal systems relevant to mechanical and closely related engineering disciplines, with attention to both physical interpretation and engineering application. Upon successful completion, students will be able to analyze and evaluate heat transfer processes in support of engineering system design. Prerequisite: ME 3335 and MATH 3323 with grades of "C" or better.

ME 3335. Engineering Fluid Mechanics.

This course introduces the fundamental principles of engineering fluid mechanics, including fluid properties, fluid statics, fluid dynamics, kinematics, control volume analysis, differential analysis, dimensional analysis, viscous pipe flow, external flows, open-channel flows, and selected turbomachinery topics. Emphasis is placed on the behavior of fluids in engineering systems and the analysis of internal and external flow applications. Prerequisite: ENGR 2302 and MATH 2393 and ME 3330 with grades of "C" or better. Corequisite: MATH 3323 with a grade of “C” or better.

ME 3351. Smart Instrumentation and Measurement.

This course covers basic concepts and principles of instrumentation and measurement systems. Students examine measurement system components such as analog and digital devices, sensors and transducers, and basic electronics to assess their utility and performance in the measurement of physical properties such as temperature, pressure, and strain. Probabilistic and statistical analysis are implemented to characterize uncertainty in processes such as data acquisition and result interpretation. Modern considerations such as wireless digital networks and communication, big data, Internet of Things (IoT), and the cybersecurity of IoT devices are also discussed. Prerequisite: ME 1101 and ENGR 3373 and ENGR 3311 and ME 3330 with grades of "C" or better. Corequisite: ME 3151 and IE 3320 with grades of “C” or better.

ME 3361. Computer Aided Design and Digital Manufacturing.

This course provides an in-depth study of computer aided design (CAD), computer aided manufacturing (CAM), and digital manufacturing. Topics include the product development process, concept development, concept generation, fundamentals of computer numerical control (CNC) machines, numerical control programming for milling processes, CNC code generation and simulation by CAD/CAM software, and an overview of other digital manufacturing processes such as additive manufacturing, laser cutting, welding, and waterjet cutting. In the lab, students get hands-on experience in reading CAD drawing standards, lab safety, machine tools operation, and operation of digital manufacturing processes, including CNC machining, additive manufacturing, and laser cutting. Prerequisite: MATH 2472 and ENGR 1304 and ENGR 2300 and ME 1101 with grades of "C" or better. Corequisite: ME 3311 with a grade of “C” or better.

ME 4131. Fluids/Thermal Lab.

This course provides laboratory study of fundamental principles in fluid mechanics, thermodynamics, and heat transfer through experiments and data analysis. Topics include temperature, pressure, and flow measurements; calibration; fluid flow and drag; pipe friction; pump performance; conduction, convection, and radiation heat transfer; heat exchangers; psychrometrics; and refrigeration cycles. Using laboratory methods, measurement systems, and data acquisition tools, students conduct experiments, analyze data, apply uncertainty analysis, and interpret results. By the end of the course, students will be able to evaluate the performance of thermal-fluid systems and communicate experimental findings in professional laboratory reports. Prerequisite: ME 3151 and ME 3331 and ME 3351 with grades of "C" or better. Corequisite: ME 4390 with a grade of "C" or better.

ME 4311. Mechanical Vibrations.

This course examines fundamental concepts of the vibration of mechanical systems with an emphasis on both analytical and computational approaches. Topics include equations of motion, free and forced vibrations of undamped and damped single- and multi-degree-of-freedom mechanical systems, self-excitation and stability analysis, application of transfer functions to vibration problems, Lagrange’s equations of motion, and determination of natural frequencies and mode shapes of multi-degree-of-freedom systems. Numerical methods such as modal estimation, modal truncation, and Fourier methods are also be discussed. Prerequisite: ENGR 2302 and [MATH 3376 or MATH 3383] and MATH 3323 with grades of "C" or better.

ME 4312. Mechanics of Composite Materials.

This course examines the deformation, stress, and strength behavior of continuous-fiber polymer-matrix laminated composites. Students analyze micromechanical models for predicting stiffness, thermal and hygrothermal expansion, and other material properties of composite laminae. The course covers classical lamination theory, including the formulation of laminate stiffness and strength, as well as environmentally induced stresses and their effects on material performance. Computational approaches are considered for evaluating laminate response, designing composite structures, and predicting effective material properties. Applications to aerospace, automotive, and advanced manufacturing systems illustrate how theoretical models inform engineering design and performance assessment. Prerequisite: [MATH 3376 or MATH 3383] and ME 3314 with grades of "C" or better.

ME 4321. Applied Finite Element Analysis.

This course provides an introduction to the finite element method (FEM). Two aspects are considered: The theoretical foundations of the method and the use of existing finite element analysis (FEA) software. Topics covered in the theory portion include the direct method, the variational method, and the weighted residuals method. Topics covered in the laboratory portion include typical pre- and post-processing modules, different types of elements, analysis of simple time independent stress analysis and heat transfer problems, and practical aspects related to the creation of a finite element model. Prerequisite: MATH 3323 and [MATH 3376 or MATH 3383] and ME 3314 all with grades of "C" or better. Corequisite: ME 3331 with a grade of "C" or better.

ME 4332. Modern Heating, Ventilating, and Air Conditioning.

This course focuses on current and emerging practices in heating, ventilating, and air conditioning (HVAC), including psychrometrics, standards, ventilation requirements, load estimation, air filtration, air sterilization, and building energy system design, simulation, and control. The scope includes both component-level analysis and whole-building performance, with emphasis on indoor air quality, energy efficiency, and regulatory and code compliance. Analytical and simulation-based design exercises are considered. Upon completion, students will be able to analyze, design, and evaluate HVAC systems for contemporary residential and commercial buildings. Prerequisite: ME 3331 with a grade of "C" or better.

ME 4341. Computational Fluid Dynamics.

This course introduces Computational Fluid Dynamics (CFD) for analyzing fluid flow and heat transfer. Topics include governing equations, numerical modeling, CFD setup, and steady-state and transient simulations. Applications cover isothermal and non-isothermal systems, incompressible and compressible flows, porous media, and rotating machinery. Using commercial CFD software, students develop skills in model setup, simulation, and interpretation of engineering results. By the end of the course, students will be able to use CFD tools to solve practical thermo-fluid problems and interpret results for engineering design. Prerequisite: MATH 3323 and [MATH 3376 or MATH 3383] and ME 3335 with grades of "C" or better.

ME 4351. Control Systems.

This course covers introductory concepts of linear control systems. Topics include block diagrams, mathematical modeling of physical systems, the Laplace transform, transfer functions, state-space representation, transient and steady state system responses, and stability. Key stability analysis techniques including the Routh-Hurwitz criterion, root locus, bode plot, and Nyquist criteria are examined. Students evaluate systems in the time and frequency domains to correlate the effect of different controller parameter choices with the corresponding system response characteristics, specifically in the design of PID controllers. Prerequisite: ENGR 2302 and MATH 3323 with grades of "C" or better.

ME 4355. Autonomous Systems and Robotics.

This course introduces different types of autonomous systems, such as autonomous driving vehicles, drones, and robots. It provides an introduction to the methods and algorithms used in the design, construction, and operation of such systems. Emphasis is placed on the application of autonomous systems, their components, and their underlying control algorithms. Topics include simultaneous localization and mapping (SLAM), sensor fusion, real-time decision-making, machine learning, information processing, path planning, localization, and intelligent control. Students combine material learned in previous courses such as dynamics and machine design with modern autonomous system algorithms to identify and analyze the complexity of real-world autonomous systems. Prerequisite: ENGR 2302 and IE 3320 and [MATH 3376 or MATH 3383] and ME 4351 with grades of “C” or better.

ME 4390. Mechanical Engineering Design I.

This course initiates the mechanical engineering capstone design experience, emphasizing problem definition, project planning, and preliminary design. Students work in teams to identify customer needs, establish engineering requirements, and develop design concepts within realistic constraints such as economic, environmental, ethical, health and safety, manufacturability, and sustainability considerations. Activities also include risk assessment and consideration of applicable engineering standards. Students also strengthen professional skills in teamwork, project management, and technical communication through written reports and oral presentations. Prerequisite: ME 3331 and ME 3314 and ME 3361 with grades of “C” or better. Corequisite: ME 4131 with a grade of "C" or better.

ME 4391. Mechanical Engineering Design II.

This course completes the mechanical engineering capstone design experience, focusing on detailed design, virtual and physical prototyping, testing, and validation. Student teams refine and implement their designs, conduct simulations and tests, analyze results, and evaluate system performance against established requirements. Emphasis is placed on iterative design improvements, integration of engineering knowledge, and consideration of societal and global impacts. Students produce a final design report and deliver formal presentations demonstrating their ability to apply engineering principles, use modern tools, and communicate effectively while adhering to professional and ethical responsibilities. Prerequisite: ME 4131 and ME 4390 with grades of "C" or better.

ME 5310. Continuum Mechanics.

This course introduces fundamental continuum mechanics concepts required for modeling the physical behavior of solids and fluids. The topics covered include indicial notation, tensor algebra, tensor calculus, rectangular Cartesian and curvilinear coordinate systems, kinematics of a continuum, strain analysis, stress analysis, basic constitutive models for solids and fluids, field equations governing continuous media, and applications to selected problems in solid and fluid mechanics. By considering constitutive models for both solids and fluids, the course establishes the foundation for a unified framework to analyze complex boundary value problems in the field of mechanical engineering.

ME 5311. Mechanical Vibrations.

This course examines fundamental concepts of the vibration of mechanical systems with an emphasis on both analytical and computational approaches. Topics include equations of motion, free and forced vibrations of undamped and damped single- and multi-degree-of-freedom mechanical systems, self-excitation and stability analysis, application of transfer functions to vibration problems, Lagrange’s equations of motion, and determination of natural frequencies and mode shapes of multi-degree-of-freedom systems. Numerical methods such as modal estimation, modal truncation, and Fourier methods are also be discussed.

ME 5312. Mechanics of Composite Materials.

This course examines the deformation, stress, and strength behavior of continuous-fiber polymer-matrix laminated composites. Students analyze micromechanical models for predicting stiffness, thermal and hygrothermal expansion, and other material properties of composite laminae. The course covers classical lamination theory, including the formulation of laminate stiffness and strength, as well as environmentally induced stresses and their effects on material performance. Computational approaches are considered for evaluating laminate response, designing composite structures, and predicting effective material properties. Applications to aerospace, automotive, and advanced manufacturing systems illustrate how theoretical models inform engineering design and performance assessment.

ME 5321. Applied Finite Element Analysis.

This course provides an introduction to the finite element method (FEM). Two aspects are considered: The theoretical foundations of the method and the use of existing finite element analysis (FEA) software. Topics covered in the theory portion include the direct method, the variational method, and the weighted residuals method. Topics covered in the laboratory portion include typical pre- and post-processing modules, different types of elements, analysis of simple time independent stress analysis and heat transfer problems, and practical aspects related to the creation of a finite element model.

ME 5332. Modern Heating, Ventilating, and Air Conditioning.

This course focuses on current and emerging practices in heating, ventilating, and air conditioning (HVAC), including psychrometrics, standards, ventilation requirements, load estimation, air filtration, air sterilization, and building energy system design, simulation, and control. The scope includes both component-level analysis and whole-building performance, with emphasis on indoor air quality, energy efficiency, and regulatory and code compliance. Analytical and simulation-based design exercises are considered. Upon completion, students will be able to analyze, design, and evaluate HVAC systems for contemporary residential and commercial buildings.

ME 5341. Computational Fluid Dynamics.

This course examines advanced principles and engineering applications of Computational Fluid Dynamics (CFD) for fluid flow and heat transfer analysis. The course covers governing equations, numerical methods, model formulation, and the selection of CFD parameters for steady-state and transient simulations. Applications include isothermal and non-isothermal systems, incompressible and compressible flows, porous media, and rotating machinery. Using commercial CFD software, students develop and assess simulation models for complex thermo-fluid problems. By the end of the course, students will be able to perform advanced CFD analyses, evaluate solution quality, and interpret results for engineering research and design.

ME 5355. Autonomous Systems and Robotics.

This course introduces different types of autonomous systems, such as autonomous driving vehicles, drones, and robots. It provides an introduction to the methods and algorithms used in the design, construction, and operation of such systems. Emphasis is placed on the application of autonomous systems, their components, and their underlying control algorithms. Topics include simultaneous localization and mapping (SLAM), sensor fusion, real-time decision-making, machine learning, information processing, path planning, localization, and intelligent control. Students implement material learned in previous courses such as dynamics and machine design along with modern autonomous system algorithms to synthesize a complex autonomous system as part of their project work.

MFGE 2132. Manufacturing Lab 1: Manufacturing Process and Digital Engineering.

This course provides hands-on laboratory experience in fundamental manufacturing processes and digital engineering tools. The scope includes interpretation of CAD drawing standards, laboratory safety procedures, operation of conventional machine tools, basic welding techniques, plastics and composites manufacturing, mechanical testing methods, and the use of Excel spreadsheets for engineering problem-solving. Emphasis is placed on practical skills development and the integration of manufacturing processes with digital tools for data analysis and documentation. The course is delivered through supervised laboratory activities and applied exercises. By the end of the course, students are expected to competently perform basic manufacturing operations and analyze experimental data using engineering software tools. Corequisite: MFGE 2332 with a grade of "D" or better.

MFGE 2332. Material Selection and Manufacturing Processes.

This course introduces the fundamentals of material processing, material selection, and process parameter determination for manufacturing applications. The scope includes material removal processes, forming, casting, polymer processing, semiconductor manufacturing, and assembly techniques, with emphasis on the relationships among material properties, process capabilities, cost, and product performance. Students examine how process variables influence quality, efficiency, and manufacturability. The course is delivered through lectures, case studies, and problem-solving activities. By the end of the course, students are expected to apply systematic approaches to select appropriate materials and manufacturing processes for engineering components. Corequisite: ENGR 1304 with a grade of "D" or better.

MFGE 3116. Manufacturing Lab 2: Computer Aided Design and Manufacturing.

This course provides hands-on laboratory experience in computer-aided design (CAD) and digital manufacturing processes. The scope includes 2D and 3D CNC machining, additive manufacturing, laser cutting, and waterjet cutting, with emphasis on the integration of CAD/CAM systems and effective process planning. Students develop digital models, generate toolpaths, and fabricate components using advanced manufacturing equipment. Students also create manufacturing drawings and apply Geometric Dimensioning and Tolerancing (GD&T) techniques to ensure that designs clearly communicate engineering intent and specify appropriate positional and dimensional tolerances for critical features. The course is delivered through supervised laboratory experiments and project-based assignments. By the end of the course, students are expected to produce functional parts from digital designs and evaluate how process parameters influence product quality, dimensional accuracy, and manufacturing efficiency. Corequisite: MFGE 3316 with a grade of "D" or better.

MFGE 3316. Computer Aided Design and Manufacturing.

This course introduces the principles and applications of Computer-Aided Design and Manufacturing (CAD/CAM) in modern product development and manufacturing. The course covers the design process; wireframe, surface, and solid modeling; and various types of technical drawings, including mono-detail and multi-detail part drawings, assembly drawings, and specification control drawings in accordance with ASME Y14.24 standards. The scope also includes process planning and the fundamentals of CNC programming for milling operations. Students learn to generate CNC code using CAD/CAM software for both 2D and 3D machining applications. The course is delivered through lectures, software-based exercises, and applied problem-solving activities that emphasize the integration of design and manufacturing. By the end of the course, students will be able to develop digital models and generate CNC programs for the manufacturing of mechanical components. Prerequisites: ENGR 1304 and ENGR 2300 and MFGE 2332 with grades of "D" or better. Corequisites: MATH 2471 with a grade of "D" or better.

MFGE 4176. Manufacturing Lab 3: Intelligent Robotics and Control.

This course provides hands-on laboratory experience in intelligent robotics, control systems, and industrial instrumentation. The scope includes industrial robot programming and applications, programmable logic controller (PLC) systems, PID control systems, sensors, actuators, and measurement devices used in manufacturing automation. Emphasis is placed on system integration, real-time control, and data acquisition in automated environments. The course is delivered through supervised laboratory experiments and applied projects using industrial-grade equipment. By the end of the course, students are expected to implement and evaluate automated control systems for manufacturing and robotic applications. Prerequisite: ENGR 3373 with a grade of "D" or better. Corequisite: MFGE 4376 with a grade of "D" or better.

MFGE 4315. Energy and Thermofluids Engineering.

This course provides a study of energy and thermofluids engineering based on fundamental principles of fluid mechanics, thermodynamics, and heat transfer. The scope includes properties of pure substances, fluid statics and dynamics, non-Newtonian fluids, differential analysis of fluid flow, viscous flow in pipes, external flows, boundary layers, open channel flows, control volume analysis of mass and energy, first and second laws of thermodynamics, steady and transient conduction, forced and natural convection, radiation, and mass transfer. The course is delivered through lectures, problem-solving sessions, and applied engineering examples. By the end of the course, students are expected to analyze thermofluid systems and apply principles to optimize energy-related processes. Prerequisite: MATH 3323 and PHYS 2326 and PHYS 2126 with grades of "D" or better.

MFGE 4318. Additive Manufacturing.

This course examines the principles, technologies, and applications of additive manufacturing (AM) with emphasis on both theory and hands-on practice. The scope includes CAD standards, historical development of AM technologies, photopolymerization, powder bed fusion, extrusion-based systems, sheet lamination, beam deposition processes, design for additive manufacturing (DfAM), and safety considerations. Students explore process–structure–property relationships and system-level implications of AM in advanced manufacturing environments. The course is delivered through lectures, case studies, and laboratory-based activities. By the end of the course, students are expected to design, analyze, and evaluate additive manufacturing solutions for complex engineering systems. Prerequisite: MFGE 2332 or ME 3161 with a grade of "D" or better.

MFGE 4330. Semiconductor Manufacturing.

This course focuses on the principles, processes, and technologies involved in modern semiconductor manufacturing. Students investigate fundamental physics, materials science, and engineering concepts that form the basis of integrated circuit fabrication. Topics include crystal growth and wafer preparation, photolithography, thin-film deposition, doping and ion implantation, etching techniques, thermal oxidation, planarization, cleanroom protocols, and contamination control. The course also covers current industry trends, yield and reliability considerations, and provides an introduction to microelectromechanical (MEMS) devices, as well as design and fabrication issues for advanced micro- and nano-systems. Prerequisite: CHEM 1341 or CHEM 1335 with a grade of "D" or better.

MFGE 4355. Design of Machine Elements and Tooling.

This course introduces the principles and systematic procedures used in the design of machine elements and manufacturing tooling. The scope of the course encompasses belt and chain drives, shafts and flexible elements, springs, welded, riveted, and brazed joints, screw fasteners, rolling-contact bearings, gears, cams and followers, as well as jigs, fixtures, gages, and geometric dimensioning and tolerancing. The course emphasizes analytical techniques, standards-based design practices, and structured problem-solving methods commonly used in mechanical and manufacturing engineering design. Prerequisite: ENGR 3311 with a grade of "D" or better. Corequisite: MFGE 3316 with a grade of "D" or better.

MFGE 4357. Dynamics of Machinery.

This course covers the principles of dynamics as applied to machinery and mechanical systems. The scope includes kinematics and kinetics of particles and rigid bodies in two and three dimensions, mechanical vibrations, linkages, gear trains, and balancing of machines, with emphasis on analysis and design of mechanical components. Students learn to model motion and forces in complex machine systems and evaluate dynamic performance. The course is delivered through lectures and analytical problem-solving exercises. By the end of the course, students are expected to analyze dynamic behavior and apply dynamics principles to the design and evaluation of machinery. Prerequisite: [ENGR 2301 or ENGR 3375] and MATH 3323 with grades of "D" or better.

MFGE 4367. Polymer Matrix Composites.

This course covers the fundamental principles of combining polymers (matrix) with reinforcing fibers to create high-strength composite materials. The primary focus is on types of polymers and reinforcements, the relationship between structure and properties, and manufacturing processes used to produce composites for applications in aerospace, automotive, and other industries. Key topics include material selection, processing techniques, structure–property relationships, physical and mechanical properties, quality assurance and testing, and design considerations. Processing methods include vacuum bag molding, lay-up methods, resin transfer molding, compression molding, filament winding, pultrusion, and automated fiber placement. A brief introduction to micromechanics is also included. Prerequisite: MFGE 2332 or TECH 4362 or ME 3361 with a grade of "D" or better.

MFGE 4376. Control Systems and Instrumentation.

This course examines the theory and application of linear control systems in manufacturing. The scope includes mathematical modeling of dynamic systems, time- and frequency-domain analysis of feedback control systems, stability analysis, transducer and sensor technologies, and fundamentals of digital control. Emphasis is placed on understanding system behavior, controller design, and performance evaluation for industrial applications. The course is delivered through lectures, analytical problem-solving, and applied case studies. By the end of the course, students are expected to model, analyze, and design control systems for manufacturing processes and instrumentation systems. Prerequisite: ENGR 2300 and PHYS 2325 and PHYS 2125 and [EE 3370 or MFGE 2332 or TECH 4362] with grades of "D" or better. Corequisite: MATH 3323 with a grade of "D" or better.

MFGE 4377. Introduction to Polymer Nanocomposites.

This course introduces polymer nanocomposites with emphasis on materials, processing, characterization, and engineering applications. The focus is primarily on nanofillers such as Nanoclay, MCNT, CNF, Nanographene platelets, Nanosilica, and Nanoalumina into polymer matrices, including dispersion mechanisms, interfacial interactions, property enhancement, and structure–property relationships. Students examine manufacturing challenges, particularly low-cost processing for industrial-scale production, as well as commercial successes and market impact of nanocomposite technologies. The course is delivered through lectures, technical discussions, and case studies of industrial applications. By the end of the course, students are expected to analyze nanocomposite systems and evaluate their performance and feasibility for real-world applications.

MFGE 4378. Introduction to Industrial Robotics.

This course introduces the fundamental principles, components, and applications of industrial robotics. The scope includes analysis of robot manipulators, kinematics, end-effectors, sensors, actuators, robot programming, and control strategies for manufacturing environments. Students explore practical considerations in selecting, operating, and integrating robots into industrial systems. The course is delivered through lectures, hands-on demonstrations, and applied problem-solving activities. By the end of the course, students are expected to analyze robotic systems, develop basic robot programs, and evaluate robot performance for automated manufacturing applications. Prerequisite: MFGE 4376 or [ME 3351 and ME 3151] with a grade of "D" or better.

MFGE 4390. Manufacturing Engineering Design I.

This course is the first in a two-course sequence focused on the integrated design and development of products and manufacturing processes. The scope includes analysis of real-world engineering problems, consideration of ethical issues in design, interaction with practicing engineers, preparation of technical reports, plans, and specifications, cost estimation, project management, and professional communication. The course emphasizes practical problem-solving, team-based projects, and application of engineering design principles. By the end of the course, students are expected to develop feasible design solutions, manage project constraints, and communicate their design rationale effectively. Prerequisites: ENGR 3311 with grade of "D" or better. Corequisite: IE 3330 with grade of "D" or better.

MFGE 4391. Manufacturing Engineering Design II.

This course is the second in a two-course sequence emphasizing implementation and refinement of integrated design and development of products and manufacturing processes. The scope includes application of ethical considerations in design, analysis of real-world engineering problems, collaboration with practicing engineers, preparation of technical reports, plans, and specifications, cost estimation, project management, and professional communication. Students work on advanced, team-based design projects to apply engineering principles and design methodologies. By the end of the course, students are expected to implement, optimize, and communicate comprehensive design solutions effectively. Prerequisites: IE 3330 and MFGE 4390 with grades of "D" or better.

MFGE 4395. AI-Based Manufacturing.

This course covers the integration of artificial intelligence (AI) and emerging digital technologies within modern manufacturing systems, with emphasis on Industry 4.0 and Industry 5.0 paradigms. The scope includes AI-driven automation, cybersecurity considerations, data analytics, machine learning, digital twins, augmented and virtual reality, cyber-physical systems, and programmable logic controllers (PLCs). The course employs a combination of conceptual analysis, systems-level modeling, and applied case studies to explore intelligent and adaptive manufacturing environments. Emphasis is placed on system integration, decision-making, and the role of AI in enhancing manufacturing performance, resilience, and sustainability. Prerequisites: MFGE 3316 and [CS 1428 or CS 1342] with grades of "D" or better.

MFGE 4396. Manufacturing Systems Design.

This course focuses on the design and analysis of manufacturing systems using simulation modeling techniques. The scope includes queuing theory, discrete-event simulation methods, and the application of simulation software to model complex manufacturing processes. Students engage in design projects to develop, implement, and analyze simulations that evaluate system performance, efficiency, and resource utilization. The course is delivered through lectures, hands-on software exercises, and project-based learning. By the end of the course, students are expected to apply simulation methods to optimize manufacturing system designs and support data-driven decision-making. Prerequisite: IE 3320 with a grade of "D" or better.