Courses for Electrical Engineering and Computer Engineering

Analog and digital communication systems, random signals, sampling, filtering, analog-to-digital encoding, advanced digital modulation/demodulation, source encoding/decoding, channel encoding/decoding, multiplexing, system performance anaylsis.

Modeling and design of communication systems. Familiarization with specialized communications equipment and techniques. Proper use of laboratory instruments.

Solid state physics for semiconductor devices, PN junction, metal semiconductor, JFET/MESFET, MOSFET, BJT, and non-ideal behaviors of solid state devices. Organic thin film devices, including organic solar cells, thin film transistors, light emitting diodes, and their application for flexible displays.

Crystal structure and defects, film nucleation and growth models, growth of polycrystaline and epitaxial fims, vacuum science technology, physical and chemical vapor deposition, solution based methods, thin film characterization techniques.

Mathematics and physics of the radiation, propagation and scattering of electromagnetic waves. Boundary value problems involving finite and infinite structures, waveguides, antennas and media.

Detailed study on the theory and operation of power electronic converters and systems. Overview of enabling power semiconductor switching devices. Introducation to feedback control of converters. Machine drives fundamentals.

Laboratory experience in three phase power systems and electric machinery. Laboratory experience on the theory and operation of power electronic converters, systems and machine drives.

Basic power systems concepts and per unit quantities; transmissions line, transformer and rotating machine modeling; power flow; symmetrical component of power systems; faulted power system analysis.

Test and analysis of power systems and machine devices and the design of systems using devices.

Static and dynamic modeling, analysis, and simulation of mechanical, electrical, hydraulic, and mixed systems. MATLAB and SIMULINK model development and simulation.

Elemental and compound semiconductors; fundamentals of semiconductors physical properties, solid state physics, optical recombination and absorption, light emitting diodes, quantum well lasers, quantum dots lasers, blue lasers, semiconductor modulators, photodetectors, semiconductor solar cells and semiconductor nanostructure devices.

Diamegnetism and Paramagnetism, Ferromagnetism, Antiferromagnetism, Ferrimagnetism, magnetic anisotropy, domains and the magnetization process, fine particles and thin films, magnetization dynamics.

Classical and modern feedback control system analysis and methods, including stability, root locus, Bode plot, frequency response, and computer analysis.

This course will provide students with practical and experimental analysis and design of feedback control systems and components, including electrical, mechanical, and electromechanical systems.

Frequency and time domain methods in discrete time control systems; sampling of continuous-time signals, stability, transform design techniques, state variable analysis, and design techniques.

Digital systems design with hardware description languages, programmable implementation technologies, electronic design automation design flows, design considerations and constraints, design for test, system on a chip designs, IP cores, reconfigurable computing and digital system design examples and applications.

Logic design and simulation via hardware description languages, use of electronic design automation tools, and CPU design.

Introduction to computer vision and digital image processing with an emphasis on image representation, transforms, filtering, compression, boundary detection, and pattern matching.

Machine learning studies methods that allow computers to learn from the data and act without being explicitly programmed. This course provides an introduction to machine learning and covers various supervised and unsupervised learning techniques, methods of dimensionality reduction, and assessment of learning algorithms.

Computer architectures, computer design, memory systems design, parallel processing concepts, supercomputers, networks, and multiprocessing systems.

Integration of microprocessors into digital systems. Includes hardware interfacing, bus protocols and peripheral systems, embedded and real-time operating systems, real-time constraints, networking and distributed process control.

Design and implementation experience with microcontrollers, interfacing, digital control systems, bus protocols and peripheral systems, real-time constraints, embedded and real-time operating systems, distribution process control.

Computational Intelligence is a discipline that relies on biologically inspired computation to solve real-world problems that otherwise are infeasible or impossible to solve using classical engineering approaches. The course will cover the fundamental techniques of computational intelligence and study practical applications in real-world engineering problems.

Advanced topics of a specialized nature.

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Fundamentals of solid state physics and quantum mechanics are covered to explain the physical principles underlying the design and operation of semiconductor devices. The second part covers applications to semiconductor microdevices and nanodevices such as diodes, transistors, lasers and photodetectors incorporating quantum structures.

Advanced quantum physics; basics of nanotechnology, molecular and nanoelectronics; fundamentals in nanophotonics; interaction of light and matter; nanostructure characterization; bionanotechnology.

Electron spin. Giant magnetoresistance theory. Spin-tunneling phenomena in magnetic tunneling junctions. Spin structure to spin electronics. Image of magnetization configuration. Magnetic materials for spin electronic devices. Spin transport to design of magnetic nandevices.

Advanced topics of a specialized nature.

This course exposes the faculty, researchers, and students in the ECE department to current research in all areas of Electrical and Computer Engineering. This seminar series focuses on science, technology, and innovation topics studied through the embedded systems, electromechanical and energy systems, devices and materials, and electromagnetics foci within the department. The seminar speakers will be invited from the ECE faculty and graduate students, national research laboratories, other universities, and industry.

Independent study; general research activities; no credit toward Ph.D.; no substitution for ECE 699. This course serves as an introduction to Ph.D.-level research prior to Ph.D. candidacy. It involves early-stage research activities to prepare students for more focused dissertation research taken as ECE 699 once admitted to Ph.D. candidacy.

This independent research course partially fulfills required doctoral level research dissertation hours toward the Ph.D. in Electrical and Computer Engineering. The course is conducted under the guidance of the Ph.D. advisor. Materials covered will be of an advanced nature aimed at providing doctoral students with an understanding of the latest research and current developments within the field. Discussion and advisor guidance will be focused on readings of research articles and development of research methodology, with the aim of producing an original research contribution that represents a novel development in the field, or a novel perspective on a pre-existing topic in the field.