Computer Engineering

Master of Science in Computer Engineering (MSCPE):  45.0 - 48.0 quarter credits
PhD: 90.0 quarter credits

About the Program

The computer engineering curriculum is designed to: (1) address the needs of students with a variety of different backgrounds; (2) ensure that graduates will have adequate knowledge and skills in at least one area of specialization; (3) meet the immediate needs of working students as well as to adequately prepare full-time students for a real-world technological environment; and (4) equip students with tools to grasp and develop new technologies and trends.

The Master of Science in Computer Engineering degree requires a minimum of 45.0 approved credits chosen in accordance with a plan of study arranged in consultation with the student's advisor and the departmental graduate advisor. Up to but not exceeding 9 research/thesis credits may be taken by students who choose to write a Master's thesis. Students who elect a non-thesis option are also encouraged to engage in research, by registering for supervised research credits (not to exceed 9 credits).

For more information, visit the Department of Electrical and Computer Engineering web site.

Admission Requirements

Applicants should preferably have an undergraduate degree equivalent to a U.S. bachelor's degree in computer engineering, computer science, or electrical engineering. Students holding degrees in other engineering and science disciplines with appropriate coursework or training will also be considered.

Appropriate coursework includes experience with all of the following: Software (advanced programming and operating systems); Computer Architecture (digital systems design, computer organization and architecture); Algorithms and Data Structures; Computer Networks. Students must have a minimum 3.0 GPA (on a 4.0 scale) for the last two years of undergraduate studies, as well as for any subsequent graduate-level work.

The GRE General Test is required of applicants to full-time MS and PhD programs. Students whose native language is not English and who do not hold a degree from a US institution must take the Test of English as a Foreign Language (TOEFL).

For additional information on how to apply, visit Drexel's Admissions page for Computer Engineering.

Master of Science in Computer Engineering

The Master of Science in Computer Engineering curriculum encompasses 45.0 or 48.0 (with the Graduate Co-op option) approved credit hours, chosen in accordance with the following requirements and a plan of study arranged with the departmental graduate advisor in consultation with the student’s research advisor, if applicable. Before the end of the first quarter in the Department of Electrical and Computer Engineering, for a full-time student, or by the end of the first year for a part-time student, said plan of study must be filed and approved with the departmental graduate advisor.

A total of at least 30.0 credit hours must be taken from among the graduate course offerings of the Department of Electrical and Computer Engineering. These credits must be taken at Drexel University. No transfer credit may be used to fulfill these requirements, regardless of content equivalency.

The remaining courses needed to reach the minimum credit hour requirement for the degree program are considered elective courses. Elective courses can be chosen from among the graduate course offerings of the Department of Electrical and Computer Engineering; other departments within the College of Engineering; the School of Biomedical Science, Engineering and Health Systems; the Department of Mathematics; the Department of Physics; the Department of Chemistry and the Department of Biology. In order to have courses outside of these departments and schools count towards degree completion, they must be approved by the departmental graduate advisors prior to registration for said courses.

Please note that ECEC 500 (Fundamentals of Computer Hardware) and ECEC 600 (Fundamentals of Computer Networks) do not count toward the credit requirements to complete the MS in Electrical Engineering degree program.

Computer Engineering (ECEC) Courses21.0
General Electrical and Computer Engineering (ECEC, ECEE, ECEP, ECES, ECET) Courses9.0
Elective Courses15.0
Total Credits45.0

 

Options for Degree Fulfillment

Although not required, students are encouraged to complete a Master’s Thesis as part of the MS studies. Those students who choose the thesis option may count up to 9.0 research/thesis credits as part of their required credit hour requirements.

Students may choose to participate in the Graduate Co-Op Program, where 6.0 credit hours can be earned for a six month co-operative education experience in industry, working on curriculum related projects. The total number of required credit hours is increased to 48.0 for those students who choose to pursue the Graduate Co-Op option. This change represents an increase in non-departmental required credit hours to a total of 18.0 credit hours, 6.0 of which are earned from the co-operative education experience.

For more information on curricular requirements, visit the Department of Electrical and Computer Engineering’s web site.

PhD in Electrical Engineering

General Requirements

The following general requirements must be satisfied in order to complete the PhD in Electrical Engineering:

  • 90.0 credit hours total
  • candidacy examination
  • research proposal
  • dissertation defense

Students entering with a master’s degree in electrical or computer engineering or a related field will be considered a post-masters PhD student and will only be required to complete a total of 45.0 credit hours, in accordance with University policy.

Curriculum

Appropriate coursework is chosen in consultation with the student’s research advisor. A plan of study must be developed by the student to encompass the total number of required credit hours. Both the departmental graduate advisor and the student’s research advisor must approve this plan.

Candidacy Examination

The candidacy examination explores the depth of understanding of the student in his/her specialty area. The student is expected to be familiar with, and be able to use, the contemporary tools and techniques of the field and to demonstrate familiarity with the principal results and key findings. 

The student, in consultation with his/her research advisor, will declare a principal technical area for the examination. The examination includes the following three parts:

  • A self-study of three papers from the archival literature in the student’s stated technical area, chosen by the committee in consultation with the student.

  • A written report (15 pages or less) on the papers, describing their objectives, key questions and hypotheses, methodology, main results and conclusions. Moreover, the student must show in an appendix independent work he/she has done on at least one of the papers – such as providing a full derivation of a result or showing meaningful examples, simulations or applications.

  • An oral examination which takes the following format:

    • A short description of the student’s principal area of interest (5 minutes, by student).
    • A review of the self-study papers and report appendix (25-30 minutes, by students).
    • Questions and answers on the report, the appendix and directly related background (40-100 minutes, student and committee).

In most cases, the work produced during the candidacy examination will be a principal reference for the student’s PhD dissertation; however, this is not a requirement.

Research Proposal

Each student, after having attained the status of PhD Candidate, must present a research proposal to a committee of faculty and industry members, chosen with his/her research advisor, who are knowledgeable in the specific area of research. This proposal should outline the specific intended subject of study, i.e. , it should present a problem statement, pertinent background, methods of study to be employed, expected difficulties and uncertainties and the anticipated form, substance and significance of the results. 

The purpose of this presentation is to verify suitability of the dissertation topic and the candidate's approach, and to obtain the advice and guidance of oversight of mature, experienced investigators. It is not to be construed as an examination, though approval by the committee is required before extensive work is undertaken. The thesis proposal presentation must be open to all; announcements regarding the proposal presentation must be made in advance. 

The thesis advisory committee will have the sole responsibility of making any recommendations regarding the research proposal. It is strongly recommended that the proposal presentation be given as soon as possible after the successful completion of the candidacy examination. The student must be a PhD candidate for at least one year before he/she can defend his/her doctoral thesis.

Dissertation Defense

Dissertation Defense procedures are described in the Office of Graduate Studies policies regarding Doctor of Philosophy Program Requirements. The student must be a PhD candidate for at least one year before he/she can defend his/her doctoral thesis.

Dual Degree

The ECE Department offers outstanding students the opportunity to receive two diplomas (BS and MS) at the same time. The program requires five (5) years to complete. Participants, who are chosen from the best undergraduates students, work with a faculty member on a research project and follow a study plan that includes selected graduate classes. This program prepares individuals for careers in research and development; many of its past graduates continued their studies toward a PhD. 

For more information on eligibility, academic requirements, and tuition policy visit the Engineering Combined BS/MS page.

Facilities

Drexel University and the Electrical and Computer Engineering Department are nationally recognized for a strong history of developing innovative research. Research programs in the ECE Department prepare students for careers in research and development, and aim to endow graduates with the ability to identify, analyze, and address new technical and scientific challenges. The ECE Department is well equipped with state-of-the-art facilities in each of the following ECE Research laboratories:  

Research Laboratories at the ECE Department

Elec & Comp Engr-Computers Courses

ECEC 500 Fundamentals Of Computer Hardware 3.0 Credits

Covers computer organization and architecture; elements of computer hardware, processors, control units, and memories; hardware for basic mathematical operations; tradeoffs between speed and complexity; examples of embedded systems; microcontrollers; systems modeling.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 501 Computational Principles of Representation and Reasoning 3.0 Credits

This course presents fundamentals of discrete mathematics as applied within the computer engineering and manufacturing environment. Students are given the theoretical background in representation and reasoning for a broad variety of engineering problems solving situations. Entity-relational techniques of representation are demonstrated to evolve into the object-oriented approach. Various search techniques are applied in the cases of representing engineering systems by using theory of automata techniques.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 502 Principles of Data Analysis 3.0 Credits

This course presents theoretical methods and techniques of model development applicable within the computer engineering design and manufacturing environment. Students are given the theoretical background in data analysis (including "data mining"). Emphasis is on hybrid systems and discrete events systems. Various methods of recognizing regularities in data will be presented. Elements of the theory of clustering and classification will be dealt with for the paradigm of software and hardware problems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 503 Principles of Decision Making 3.0 Credits

This course presents theoretical fundamentals and engineering techniques of decision making and problem solving applicable within the computer engineering design and manufacturing environment. Students are given the theoretical background in optimization methods for a broad variety of situation. Elements of the theory of planning and on-line control of systems are presented within the scope of software and hardware computer design and control.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 511 Combinational Circuit Design 3.0 Credits

Representing arithmetic. Logic and syntax data for machine processing. Switching algebra: Boolean and multiple values. Identification and classification of functions. Realizing completely specified and incompletely specified Boolean functions. Issues in designing large communication/control Boolean functions. Fault and testing of Boolean function.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 512 Sequential Circuit Design 3.0 Credits

Finite automata and their realization by sequential machines, capabilities, transformation, and minimization of finite automata, linear finite automata. Clocked pulsed and level mode sequential circuits. Malfunctions in sequential circuits: hazards, races, lockouts, metastability. Issues of state assignment. Evolution of memory elements design: ROM vs. RAM vs. associative memory.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 511 [Min Grade: C]

ECEC 513 Design for Testability 3.0 Credits

Economics vs. Complexity vs. Strategy of Testing; Fault Models; Test Generation; Testability Analysis & Designing Testable Circuits; Testing Microprocessors, Memories and Computer Components; Test Data Compression; Fault Tolerant Hardware; Reliably vs. Availability; Redundancy and Error Correcting Codes.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 511 [Min Grade: C] and ECEC 512 [Min Grade: C]

ECEC 520 Dependable Computing 3.0 Credits

Fundamental design issues involved in building reliable, safety-critical, and highly available systems. Topics include testing and fault-tolerant design of VLSI circuits, hardware and software fault tolerance, information redundancy, and fault-tolerant distributed systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 541 Robotic Computer Interface Controls I 3.0 Credits

Covers sensors, actuators, mechanical components of robots, kinematics, inverse kinematics, dynamics, and equations of motion.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 542 Robotic Computer Interface Controls II 3.0 Credits

Covers the robot control problem, including PD, PID, position, force and hybrid controllers, resolved rate and acceleration control, and multiprocessor architecture.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 641 [Min Grade: C] and ECES 643 [Min Grade: C] and ECEC 541 [Min Grade: C]

ECEC 543 Robotic Computer Interface Controls III 3.0 Credits

Covers non-linear control techniques, FLDT, and advanced topics.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 542 [Min Grade: C]

ECEC 600 Fundamentals of Computer Networks 3.0 Credits

Fundamentals design principles of ATM, Internet and local area networks; protocol layers and the Internet Architecture; medium access protocols; application protocols and TCP/IP utilities; basic principles and virtual circuit switching; naming and addressing; flow and congestion control protocols; routing algorithms; Quality-of-Service in computer networks; security issues in networks.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 621 High Performance Computer Architecture 3.0 Credits

Maximizing single processor performance. Concepts and techniques for design of computer systems. Processor design, instruction set architecture design and implementation, memory hierarchy, pipelines processors, bus bandwidth, processor/memory interconnections, cache memory, virtual memory, advanced I/O systems, performance evaluation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 622 Parallel Computer Architecture 3.0 Credits

Advanced techniques of computer design. Use of parallel processing to achieve high performance levels. Fine and coarse grained parallelism. Multiple CPU parallelism, through multiprocessors, array and vector processors. Dataflow architectures and special purpose processors. Design implications of memory latency and bandwidth limitations. Speedup problems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 621 [Min Grade: C]

ECEC 623 Advanced Topics in Computer Architecture 3.0 Credits

This course teaches advanced concepts of modern computer architecture and introduces the current challenges faced by computer architects. These challenges include power consumption, transistor variability, and processor heterogeneity. Students develop their research skills through a self directed research project with a final presentation and conference style writeup.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 621 [Min Grade: C]

ECEC 631 Principles of Computer Networking 3.0 Credits

Principles of circuit switching, packet switching and virtual circuits; protocol layering; application layer protocols for e-mail and web applications; naming and addressing; flow control and congestion avoidance with TCP; Internet Protocol (IP); routing algorithms; router architectures; multicast protocols; local area network technologies and protocols; issues in multimedia transmissions; scheduling and policing; Quality-of-Service and emerging Internet service architectures; principles of cryptography.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 632 Performance Analysis of Computer Networks 3.0 Credits

Covers probability theory and its applications to networks, random variable and random processes; Markov chains, multi-dimensional Markov chains; M/M/1, M/M/m, M/M/m/m, M/G/1 and G/G/1 queueing systems and their applications in computer networks; analysis of networks of queues: Kleinrock Independence Approximation; Time-reversibility and Burke's theorem; Jackson's theorem; the phenomenon of long-range dependence and its implications in network design and traffic engineering.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 631 [Min Grade: C]

ECEC 633 Advanced Topics in Computer Networking 3.0 Credits

perspectives in the areas of switch/router architectures, scheduling for best-effort and guaranteed services, QoS mechanisms and architectures, web protocols and applications, network interface design, optical networking, and network economics. The course also includes a research project in computer networking involving literature survey, critical analysis, and finally, an original and novel research contribution.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 631 [Min Grade: C] and ECEC 632 [Min Grade: C]

ECEC 654 Knowledge Engineering I 3.0 Credits

Covers conceptual modeling, including an overview of knowledge representation. Includes semantic networks, reduced semantic networks, logic of incomplete knowledge bases, extensional semantic networks, and applications of conceptual models.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 655 Knowledge Engineering II 3.0 Credits

Covers expert systems, including language and tools of knowledge engineering. Includes reasoning about reasoning, design and evaluation, heuristics in expert systems, expert systems for decision support, and expert systems in conceptual design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 654 [Min Grade: C]

ECEC 656 Knowledge Engineering III 3.0 Credits

Covers information-intensive systems, including information representation in autonomous systems. Includes clauses and their validation; clustering in linguistic structures; linguistic and pictorial knowledge bases; discovery in mathematics, including am; and methods of new knowledge generation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 655 [Min Grade: C]

ECEC 661 VLSI Design 3.0 Credits

Covers CMOS design styles, techniques, and performance; VLSI computer hardware, arithmetic units, and signal processing systems; and cat tools for layout design and simulation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 662 VLSI Array Processors I 3.0 Credits

Covers VLSI testing, including design for testability and parallel computer architectures; signal and image processing algorithms and mapping algorithms onto array structures; and systolic array processors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 661 [Min Grade: C]

ECEC 663 VLSI Array Processors II 3.0 Credits

Covers wavefront array processors; matching hardware to arrays; hardware design, systems design, and fault-tolerant design; and implementations and VLSI design projects.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 662 [Min Grade: C]

ECEC 671 Electronic Design Automation for VLSI Circuits I 3.0 Credits

This course focuses on the electronic design automation problems in the design process of VLSI integrated circuits. In this first quarter of the course, algorithms, techniques and heuristics structuring the foundations of contemporary VLSI CAD tools are presented. Boolean algebra, graph theory, logic minimization and satisfiability topics are presented.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEC 672 Electronic Design Automation for VLSI Circuits II 3.0 Credits

This course focuses on the electronic design automation problems in the design process of VLSI integrated circuits. In this second quarter of the course, physical VLSI design steps of technology mapping, floor planning, placement, routing and timing and presented individual and team-based small-to-medium scale programming projects are assigned.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 671 [Min Grade: C]

ECEC 673 Deep Sub-Micron Integrated Circuit Design 3.0 Credits

This course focuses on the design challenges of digital VLSI integrated circuits in deep sub-micron manufacturing technologies. Automation challenges and high-performance circuit design techniques such as low-power and variation-aware design are presented. The course material is delivered in a lecture format structured on recent presentations, articles, and tutorials.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 671 [Min Grade: C]

ECEC 690 Special Topics Computer Engineering 9.0 Credits

Covers special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 697 Research in Computer Engineering 1.0-12.0 Credit

Research in computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 699 Supervised Study in Computer Engineering 9.0 Credits

Supervised study in computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 890 Advanced Special Topics in Computer Engineering 1.0-9.0 Credit

Covers advanced special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 891 Advanced Topics in Computer Engineering 0.5-9.0 Credits

Advanced topics in computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 898 Master's Thesis in Computer Engineering 1.0-12.0 Credit

Master's thesis in computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 997 Dissertation Research in Computer Engineering 1.0-12.0 Credit

Graded Ph.D. dissertation in computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEC 998 Ph.D. Dissertation in Computer Engineering 1.0-12.0 Credit

Ph.D. dissertation in computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

Elec & Computer Engr-Electroph Courses

ECEE 501 Physical Principles of Electrical Engineering I 3.0 Credits

Core course. Covers classical mechanics, including generalized coordinates, Lagrangian and Hamiltonian formulation, and variational principle. Introduces quantum mechanics, including Schrodinger equation, wave functions, operators, expectation values, and hydrogen atom.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 502 Physical Principles of Electrical Engineering II 3.0 Credits

Core course. Continues ECEE 501. Covers atomic orbitals, angular momentum, oscillators, time-independent and time-dependent perturbation theories, many-particle wave functions, and optical transitions. Also covers statistical mechanics, including distributions, ensembles, and thermal properties of solids.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 501 [Min Grade: C]

ECEE 507 Electromagnetic Field Analysis I 3.0 Credits

Core course. Covers Maxwell's equations; solutions of Laplace's equation, Green's function, and scalar and vector potentials; energy and momentum in electromagnetic fields; and interaction of fields and material media.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 508 Electromagnetic Field Analysis II 3.0 Credits

Core course. Continues ECEE 507. Covers em waves, including reflection, refraction, polarization, and dispersion. Includes metallic and dielectric guiding structures, guides, and waveguide circuits and applications to stripline, microstrip, and optical fiber transmission systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 507 [Min Grade: C]

ECEE 510 Scattering & Diffraction of Electromagnetic Waves 3.0 Credits

Boundary value problems of EM theory. Exact and approximate methods for scattering by spheres, half plane, slit; radar cross-section theory. Quasi-optical theory, scattering, diffraction coefficients. Applications to radio propagation around the earth.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 517 Microwave Networks & Transmission Media 3.0 Credits

Core course. Atmospheric wave propagation, solution of wave equation without sources in isotropic media, plane-waves, polarization, dispersion surfaces, wave admittance and impedance, wave propagation in free-space and various media, waves at interfaces, solution of wave equation with sources, duality principle, arrays analysis, metallic waveguides, modes in cylindrical waveguides, rectangular and circular, resonant cavities and perturbational methods.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 518 Microwave Passive Components 3.0 Credits

Core course. V-I and E-H analogy, Kirchoff's Law, Telegrapher's EQ, voltage and current waves, reflection coefficient and impedance relationship, Smith Chart, impedance matching techniques, Bode-Fano theoretical limit, Broadband Quarter-wave Transformer, N-port linear networks, Z, Y, and S parameters, ABCD and T matrices, signal flow-graph and transfer functions, synthesis of two-port and unitary properties, even-odd mode analysis and dual directional couplers (design and synthesis), periodic structures and Flouke modes, filter design and synthesis using insertion loss and image methods, prototype LO filter and transformation to LP, BP, HP, and BS filters, Richards transform and Kuroda identities.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 519 Microwave Active Subsystems 3.0 Credits

Core course. Overview of physics of P-N junction and Schottky junctions, pin, varactor, and step recovery diodes and their applications, transistors, MESFET and HEMT, BJT and HBT passive microwave circuits: switches, detectors, attenuators, modulators, and phase shifter, active microwave circuits: LNA, power amplifier, distributed amplifier, oscillators (fixed and VCO) power budget and link performance calculations for telecommunication, radar, and EW systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 520 Solid-State Electronics 3.0 Credits

This course familiarizes the students with the fundamental properties of semiconductor materials leading to the students of electronic and photonic devices. Covered topics include: atomic structure, crystal structure, theories of electron conduction, scattering, pn junctions, heterojunctions, metal-semiconductor contacts, and junction devices.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 521 Bipolar and FETs 3.0 Credits

This is the second course in a sequence of three on electronic and photonic devices. The course covers families of electronic devices. The course covers various families of electronic devices based on silicon and compound semiconductors. Bipolar transistors such as BJTs and HBTs and field-effect devices such as MOSFETs, MESFETs, and MODFETs are studied.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 520 [Min Grade: C]

ECEE 522 Photonic Devices 3.0 Credits

Covers fundamentals of absorption, spontaneous, and stimulated emission, photodetectors, light emitting diodes, laser oscillation, semiconductor laser diodes, RIN and phase noise, quantum well lasers, optical receivers, and quantum effect devices.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 521 [Min Grade: C]

ECEE 523 Integrated Circuits 3.0 Credits

Covers growth of single-crystal silicon, growth of oxide and epitaxial layers, photolithography, diffusion of impurities, fabrication of bipolar and unipolar integrated circuits, and interconnections and packaging.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 521 [Min Grade: C]

ECEE 525 Digital IC and CMOS Technology 3.0 Credits

Covers digital ICs using CMOS technology. Transistor level building blocks, -NOT, NAND, NOR, XOR, OAI, and AOI ? are designed using industry standard CAD tools, e.g. Cadence. Circuit topologies such as CPL, transmission gates are explored. CMOS technology/fabrication and layout are discussed to optimize speed, power, and area.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 526 Custom VLSI Design 3.0 Credits

Course covers advanced design styles such as dynamic CMOS circuits, low power circuit concepts, bi-CMOS circuits and the design of VLSI sub-systems. A major category is memory design, both DRAM. VLSI design styles, system integration aspects are discussed. Project design involves a fair amount of layout.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 525 [Min Grade: C]

ECEE 541 Photonic Systems 3.0 Credits

Introduction to Optical principles through EM theory. Covers the mathematics of wave motion, as well as the idea of light propagating as particles. The course shows how ray (or geometrical) optics and Gaussian optics are derived from the wave theory. The course also introduces the polarization of light, and how this effects optical propagation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 542 Optical Applications of Diffraction and Interference 3.0 Credits

Optical Applications of Diffraction and Interference. This course is an introduction to optical principles through EM theory. Covered topics include wave motion and superposition. Introduction to optical interference, or the interaction of light with itself. Topics include interference and interferometers, diffraction, and Fourier Optics. Diffraction topics include, far (Fraunhofer), near (Fresnel), and the near-near field diffraction. The course includes coding of some of the classical diffraction algorithms for the use in a project.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 603 Cooperative Phenomena 3.0 Credits

Covers dielectrics, ferroelectrics, diamagnetism, paramagnetism, ferromagnetism, and antiferromagnetism; superconductivity, London's equations, BCS theory, and Josephson effect; and flux quantization, hard superconductors, GLAG theory, flux dynamics, and high-temperature superconductors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 502 [Min Grade: C] and ECEE 503 [Min Grade: C]

ECEE 607 Nanoscale Fields 3.0 Credits

Course covers essentials of electric and magnetic fields, including thermodynamics of polarizable media. Emphasis is on nano-and micro-scale effects like Van der Waals and double layer interactions, plasmon resonance and others. Examples from colloids and other areas of nanotechnology are used to illustrate main ideas.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 619 Radio Frequency Integrated Circuit Design 3.0 Credits

This course introduces concepts in design of radio frequency (microwave and millimeter wave) integrated circuits. Optimum transistor technologies based on unipolar (MOS, FET, HEMT) and bipolar (BJT.HBT) are discussed for various RFIC applications. Performance of devices and circuits are evaluated in terms of gain, noise, and linearity. Active circuits and systems used in a variety of communications, imaging, and sensing are discussed in terms of standards and applications. IC design projects are integral to this course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 518 [Min Grade: C]

ECEE 621 Thin Film Technology I 3.0 Credits

Covers vacuum technology, plasma processing, VLSI fabrication, and thin film technologies (e.g., plasma etching, thin film deposition, and thin film characterizations).

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 622 Microfabrication Technology 3.0 Credits

The course provides an overview of basic technological processes typically involved in microfabrication of Micro-Electro-Mechanical Systems (MEMS). The course includes several demonstration laboratories involving basic photolithography, thin film depositions and electroplating.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 623 Thin Film Technology III 3.0 Credits

Presents speakers on state-of-the-art practice and future applications of thin film deposition and processing technology.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 622 [Min Grade: C]

ECEE 641 Fiber Optics & Optical Communications I 3.0 Credits

Covers propagation in guided and unguided media, including step and graded fibers, dispersion, guide deformations, and mode coupling. Involves design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 642 Fiber Optics & Optical Communications II 3.0 Credits

Covers coupling devices, multimode guides, sources, lasers, and radiation patterns. Includes reliability, detectors, circuit models, and noise.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 641 [Min Grade: C]

ECEE 671 Seminar in Electro-Physics I 2.0 Credits

Advanced graduate seminar. Focuses on recent developments in microwaves, electro-optics, and solid-state devices.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 672 Seminar in Electro-Physics II 2.0 Credits

Continues ECEE 671.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 673 Seminar in Electro-Physics III 2.0 Credits

Continues ECEE 672.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 690 Special Topics in Electrophysics 9.0 Credits

Covers special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEE 697 Research in Electrophysics 1.0-12.0 Credit

Research in electrophysics.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEE 699 Supervised Study in Electrophysics 0.5-9.0 Credits

Supervised study in electrophysics.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEE 811 Microwave & THZ Photonics I 3.0 Credits

This course focuses on high speed photonic components for microwave and terahertz fiber-optic links, namely high speed lasers, external modulators and photodetectors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEE 812 Microwave & THZ Photonics II 3.0 Credits

This course focuses on high speed analog and digital fiber-optic links including loss and dynamic range calculations.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 811 [Min Grade: C]

ECEE 813 Microwave & THZ Photonics III 3.0 Credits

This course focuses on the applications of fiber-optic links; antenna remoting, optically fed and controlled phased array antennas and fiber radio.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 811 [Min Grade: C] and ECEE 812 [Min Grade: C]

ECEE 820 Carrier Transport Fundamentals 3.0 Credits

This course introduces the fundamentals of carrier transport in semiconductors, beyond the common drift-diffusion description functions and Boltzmann transport equations are covered. Monte Carlo simulations are used for low field and high field transport studies.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 520 [Min Grade: C]

ECEE 821 Nanoelectronics 3.0 Credits

Focus is on current transport when the size of electronic medium reaches nanometer scales, that is, deBrogile wavelength. Topics include: characteristic lengths, magneto-electric subbands, conductance from transmission, resistance in a ballistic conductor, quantum Hall effect, electron scattering in quantum structures.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 820 [Min Grade: C]

ECEE 890 Advanced Special Topics in Electrophysics 1.0-9.0 Credit

Covers advanced special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEE 898 Masters Thesis in Electrophysics 9.0 Credits

Master's thesis in electrophysics.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEE 997 Dissertation Research in Electrophysics 1.0-12.0 Credit

Graded Ph.D. dissertation in electrophysics.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEE 998 Ph.D. Dissertation in Electrophysics 1.0-12.0 Credit

Ph.D. dissertation in electrophysics.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

Elec & Computer Engr-Power Eng Courses

ECEP 501 Power System Analysis 3.0 Credits

Core course. Covers modeling of power systems, including: symmetrical components, transmission lines, transformers, per-unit values and one-line diagrams. Introduces power flow. Required of first-year power majors; equivalent undergraduate credits may be substituted.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEP 502 Computer Analysis of Power Systems 3.0 Credits

Core course. Covers digital computation methods, including load flow, fault, and transient stability problems. Required of first-year power engineering majors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 501 [Min Grade: C]

ECEP 503 Synchronous Machine Modeling 3.0 Credits

Core course. Covers two-reaction theory, Park's synchronous machine models, modeling of the synchronous machine excitation and governor systems, and the effects on power system stability. Required of first-year power engineering majors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 502 [Min Grade: C]

ECEP 601 Modeling & Analysis of Power Distribution Systems 3.0 Credits

Modeling and Analysis of Power Distribution Systems. Introduction to power distribution system; balanced and unbalanced systems, component and load modeling, radial and weakly meshed topologies; algorithms for unbalanced power flow studies including radial and general structure solver.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Corequisite: ECEP 501

ECEP 602 Power Distribution Automation and Control 3.0 Credits

Power Distribution Automation and Control. Focuses on distribution management systems and their application: including optimizing network operation -capacitor placement and control, network reconfiguration, service restoration. Modern solution technology will be addresses.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Corequisite: ECEP 502

ECEP 603 Service and Power Quality in Distribution Systems 3.0 Credits

Service and Power Quality in Distribution Systems. Focus power distribution systems: service and power quality assessment including stat estimation, voltage quality, trouble call analysis, service restoration, component and system reliability assessment.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEP 610 Power System Dynamics 3.0 Credits

Covers system parameters and dynamics, swing equation and solutions for two-machine and multimachine systems, equal area criterion, computer solution techniques, system effects due to dynamic behavior of particular system components, and load characteristics.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 503 [Min Grade: C]

ECEP 611 Power System Security 3.0 Credits

Covers contingency analysis, including operating and security constraints and network sensitivities; corrective dispatch using linear programming; and state estimation, including network observability, detection, and identification of bad data.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 610 [Min Grade: C]

ECEP 612 Economic Operation of Power Systems 3.0 Credits

Covers unit characteristics and economic operation, including transmission loss coefficients, general loss formula, and automatic economic load dispatch.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 501 [Min Grade: C]

ECEP 613 Advanced Power System Design 3.0 Credits

Covers components, functions, application, and performance; relative cost and scaling parameters; overall planning problem considering present-worth and cost-benefit principles; system reliability; intersystem pooling; and growth.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEP 641 Protective Relaying 3.0 Credits

Covers relay principles and types, instrumentation of system parameters, relay characteristics and response, system component protection, solid-state relaying, underfrequency relays, and load shedding.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 503 [Min Grade: C]

ECEP 642 Protective Relay Laboratory 3.0 Credits

Covers electromechanical and static relays. Emphasizes application based on observed performance. Includes testing.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 641 [Min Grade: C]

ECEP 643 Solid State Protective Relaying 3.0 Credits

Covers solid-state protective relays as applied to power system stability and protection, including comparisons with electromechanical relays.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 641 [Min Grade: C]

ECEP 661 High Voltage High Power Phenomena 3.0 Credits

Covers corona, corona losses, electromagnetic noise, dielectric strength, lightning, impulse testing and safety practices, elements of high-power circuit interruption, circuit and physical phenomena, and circuit breakers.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEP 671 AC-DC and DC-AC Power Electronic Converters 3.0 Credits

AC-DC and DC-AC Power Electronic Converters. Study of basic power electronic converter circuits: diode and phase controlled rectifiers and inverters; switch-mode converters. Applications to DC and AC power supplies.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 501 [Min Grade: C] and ECEP 601 [Min Grade: C]

ECEP 672 Power Electronic Experiments: Hardware and Software 3.0 Credits

Hardware and Software Lab-Intensive course. Additional lectures on: Study of DC-DC switch-mode converters; Study of power electronic circuitry in residential, industrial and electric utility applications; Optimizing utility interfaces with power electronic systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 671 [Min Grade: C]

ECEP 673 Power Electronic Applications 3.0 Credits

Electric Utility Applications with emphasis on DC Transmission, Optimizing the Utility interface. Resonant converters. Fundamentals of motor drives and their controls: induction, DC, synchronous and specialized motors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 671 [Min Grade: C]

ECEP 690 Special Topics in Power Engineering 9.0 Credits

Covers special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 697 Research in Power Engineering 0.5-9.0 Credits

Research in power engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 699 Supervised Study in Power Engineering 9.0 Credits

Supervised study in power engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 801 Advanced Topics in Power Systems I 0.5-9.0 Credits

Discusses the latest innovations, theories, and methodologies for the design, planning, and operation of power systems. Requires students to read and discuss technical articles published in the IEEE Transactions on pas, the Journal of Electric Energy and Systems, and other publications.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 802 Advanced Topics in Power Systems II 3.0 Credits

Continues ECEP 801.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEP 803 Advanced Topics in Power Systems III 3.0 Credits

Continues ECEP 802.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECEP 821 Load Forecasting & Probability Methods 3.0 Credits

Reviews probability methods. Covers probabilistic generation and load models; forecasting methodologies; load classification and characterization; energy and peak demand forecasting; weather-and non-weather-sensitive forecast; and annual, monthly, weekly, and daily forecast.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 610 [Min Grade: C]

ECEP 822 Power System Planning 3.0 Credits

Covers deterministic planning, including automated transmission system expansion planning and network sensitivities, and probabilistic planning, including generation and load models, generation cost analysis, production costing, and energy production cost models for budgeting and planning.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 821 [Min Grade: C]

ECEP 823 Power System Reliability 3.0 Credits

Covers basic reliability concepts, including probabilistic generation and load models, loss of load probability (LOLP), static and spinning generating-capacity reliability, transmission system reliability, and composite system and interconnected system reliability.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 822 [Min Grade: C]

ECEP 890 Advanced Special Topics in Power Engineering 1.0-9.0 Credit

Covers advanced special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 898 Master's Thesis Power Engineering 1.0-12.0 Credit

Master's thesis in power engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 997 Dissertation Research in Power Engineering 1.0-12.0 Credit

Graded Ph.D. dissertation in power engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECEP 998 Ph.D. Dissertation in Power Engineering 1.0-12.0 Credit

Ph.D. dissertation in power engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

Elec & Computer Engr-Systems Courses

ECES 510 Analytical Methods in Systems 3.0 Credits

This course is intended to provide graduate student in the field of signal and image processing with the necessary mathematical foundation, which is prevalent in contemporary signal and image processing research and practice.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 511 Fundamentals of Systems I 3.0 Credits

Core course. Covers linear operators, including forms and properties (differential equations, transfer function, state space, causality, linearity, and time invariance); impulse response, including convolution, transition matrices, fundamental matrix, and linear dynamical system; definition, including properties and classification; representation, including block diagrams, signal flow, and analog and digital; properties, including controllability and observability; and eigenstructure, including eigenvalues and eigenvector and similarity transformations.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 512 Fundamentals of Systems II 3.0 Credits

Core course. Covers realization and identification, including minimal realization, reducibility and equivalence of models, and identification of systems; stability, including bounded input-bounded output, polynomial roots, and Lyapunov; and feedback compensation and design, including observers and controllers and multi-input/multi-output systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 511 [Min Grade: C]

ECES 513 Fundamentals of Systems III 3.0 Credits

Core course. Covers multivariable systems, numerical aspects of system analysis and design, design of compensators, elements of robustness, and robust stabilization.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 512 [Min Grade: C]

ECES 521 Probability & Random Variables 3.0 Credits

Probability concepts. Single and multiple random variables. Functions of random variables. Moments and characteristic functions. Random number and hypothesis testing. Maximum likelihood estimation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 522 Random Process & Spectral Analysis 3.0 Credits

Random Process. Poisson Process, Shot Noise. Gaussian Process. Matched Filters. Kalman Filters. Power Spectral Density. Autocorrelation and cross correlation. PSD estimation. Entropy. Markov Processes. Queuing Theory.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 521 [Min Grade: C]

ECES 523 Detection & Estimation Theory 3.0 Credits

Detection of signals in noise. Bayes criterion. NP criterion. Binary and M_ary hypotheses. Estimation of signal parameters. MLE and MAP estimation. 1D and 2D signals. ROC Analyses. Decision fusion.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 521 [Min Grade: C] and ECES 522 [Min Grade: C]

ECES 558 Digital Signal Processing for Sound & Hearing 3.0 Credits

Introduction to the computational modeling of sound and the human auditory system. Signal processing issues, such as sampling, aliasing, and quantization, are examined from an audio perspective. Covers applications including audio data compression (mp3), sound synthesis, and audio watermarking.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 631 [Min Grade: C]

ECES 559 Processing of the Human Voice 3.0 Credits

Introduction to the computational modeling of the human voice for analysis, synthesis, and recognition. Topics covered include vocal physiology, voice analysis-synthesis, voice data coding (for digital communications, VoIP), speaker identification, speech synthesis, and automatic speech recognition.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 631 [Min Grade: C] and ECES 558 [Min Grade: C]

ECES 561 Medical Robotics I 3.0 Credits

This course will introduce the emerging, multidisciplinary field of medical robotics. Topics include: introduction to robot architecture, kinematics, dynamics and control; automation aspects of medical procedures; safety, performance limitations; regulatory and economics and future developments.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 512 [Min Grade: C]

ECES 562 Medical Robotics II 3.0 Credits

This course will continue the introduction to the emerging, multidisciplinary field of medical robotics. Topics include: medical procedure automation; robot testing and simulation techniques; This is a project based course that will afford students the opportunity to work with existing medical robotic systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 561 [Min Grade: C]

ECES 604 Optimal Estimation & Stochastic Control 3.0 Credits

Introduction to control system problems with stochastic disturbances; linear state space filtering, Kalman Filtering, Non-linear systems; extended Kalman Filtering. Robust and H-infinity methods.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 512 [Min Grade: C] and ECES 521 [Min Grade: C]

ECES 607 Estimation Theory 3.0 Credits

General characteristics of estimators. Estimators: least squares, mean square, minimum variance, maximum a posteriori, maximum likelihood. Numerical solution. Sequential estimators.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 614 Passive Network Synthesis 3.0 Credits

An introduction to approximation theory; driving point functions; realizability by lumped-parameter circuits; positive real functions; properties of two and three element driving point functions and their synthesis; transfer function synthesis; all-pass networks.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 615 Analysis & Design of Linear Active Networks 3.0 Credits

DC and AC models of bipolar transistors and FETs; design of differential operational amplifiers; optimal design of broad-band IC amplifiers; design of tuned amplifiers; design for optimal power gain, distortion, and efficiency; noise in transistor circuits.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 621 Communications I 3.0 Credits

Covers modulation techniques: baseband PAM, passband PAM, QAM, and PSK; orthogonal signaling: FSK; symbol/vector detection: matched filter and correlation detector; sequence detection: ISI; equalization: adaptive and blind; carrier synchronization; and timing recovery.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 622 Communications II 3.0 Credits

Covers shot noise, noise in detectors, analog fiberoptic systems, carrier and subcarrier modulation, digital systems bit error rates for NRZ and RZ formats, coherent optical communication systems-heterodyne and homodyne systems, wavelength division multiplexing, system design concepts, power budgets, rise time budgets, and optical switching networks.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 623 Communications III 3.0 Credits

Covers fundamentals of information theory: information measure, entropy, and channel capacity; source encoding and decoding; rate distortion theory; linear codes; block codes; convolutional codes, Viterbi algorithm; encryption and decryption; and spread spectrum communications.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 631 Fundamentals of Deterministic Digital Signal Processing 3.0 Credits

Fundamentals of Deterministic Digital Signal Processing. This course introduces the fundamentals of deterministic signal processing.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 632 Fundamentals of Statistical Digital Signal Processing 3.0 Credits

Fundamentals of Statistical Deterministic Digital Signal Processing. The course covers topics on statistical signal processing related to data modeling, forecasting and system identification.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 631 [Min Grade: C]

ECES 640 Genomic Signal Processing 3.0 Credits

This course focuses on signal processing applied to analysis and design of biological systems. This is a growing area of interest with many topics ranging from DNA sequence analysis, to gene prediction, sequence alignment, and bio-inspired signal processing for robust system design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 642 Optimal Control 3.0 Credits

Introduces the concept of optimal control first by static optimization for state space formulated systems. The concept is expanded as the linear quadratic regulator problem for dynamic systems allowing solution of the optimal control and suboptimal control problems for both discrete and continuous time. Additional topics include the Riccati equation, the tracking problem, the minimum time problem, dynamic programming, differential games and reinforcement learning. The course focuses on deriving, understanding, and implementation of the algorithms.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 512 [Min Grade: C]

ECES 643 Digital Control Systems Analysis & Design 3.0 Credits

Covers analysis and design of sampled-data control system using Z-transform and state-variable formulation, sampling, data reconstruction and error analysis, stability of linear and non-linear discrete time systems by classical and Lyapunov's second method, compensator design using classical methods (e.g., rootlocus) and computer-aided techniques for online digital controls, optimal control, discrete-time maximum principle, sensitivity analysis, and multirate sampled-data systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 513 [Min Grade: C]

ECES 644 Computer Control Systems 3.0 Credits

Introduction to the fundamentals of real-time controlling electromechanical dynamic systems, including modeling, analysis, simulation, stabilization and controller design. Control design approaches include: pole placement, quadratic and robust control performances.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 651 Intelligent Control 3.0 Credits

Concepts of Intelligence in Engineering Systems, Learning Automation, Principles of Knowledge Representation. Levels of Resolution and Nestedness. Organization of Planning: Axioms and Self-Evident Principles.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 660 Machine Listening and Music IR 3.0 Credits

This course introduces methods for the computational analysis, recognition, and understanding of sound and music from the acoustic signal. Covered applications include sound detection and recognition, sound source separation, artist and song identification, music similarity determination, and automatic transcription.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 631 [Min Grade: C]

ECES 670 Seminar in Systems I 2.0 Credits

Involves presentations focused on recent publications and research in systems, including communications, controls, signal processing, robotics, and networks.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 671 Seminar in Systems II 2.0 Credits

Continues ECES 670.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 672 Seminar in Systems III 2.0 Credits

Continues ECES 671.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 681 Fundamentals of Computer Vision 3.0 Credits

Develops the theoretical and algorithmic tool that enables a machine (computer) to analyze, to make inferences about a "scene" from a scene's "manifestations", which are acquired through sensory data (image, or image sequence), and to perform tasks.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 682 Fundamentals of Image Processing 3.0 Credits

The course introduces the foundation of image processing with hands-on settings. Taught in conjunction with an imaging laboratory.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 631 [Min Grade: C]

ECES 684 Imaging Modalities 3.0 Credits

This course is intended to produce students and image processing with a background on image formation in modalities for non-invasive 3D imaging. The goal is to develop models that lead to qualitative measures of image quality and the dependence of quality imaging system parameters.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 685 Image Reconstruction Algorithms 3.0 Credits

This course is intended to provide graduate students in signal and image processing with an exposure to the design and evaluation of algorithms for tomographic imaging.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 684 [Min Grade: C] and BMES 621 [Min Grade: C]

ECES 690 Special Topics in Systems Engineering 9.0 Credits

Covers special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 697 Research In Systems Engineering 1.0-12.0 Credit

Research in systems engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 699 Supervised Study in Systems Engineering 9.0 Credits

Supervised study in systems engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 801 Advanced Topics in Systems I 3.0 Credits

Familiarizes students with current research results in their field of interest, specifically in works reported in such journals as The IEEE Transactions.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 802 Advanced Topics in Systems II 3.0 Credits

Continues ECES 801.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 803 Advanced Topics in Systems III 3.0 Credits

Continues ECES 802.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 811 Optimization Methods for Engineering Design 3.0 Credits

Applications of mathematical programming and optimization methods in engineering design problems such as networks, control, communication, and power systems optimization. Optimization problem definition in terms of objective function, design variables, and design constraints. Single variable and multivariable search methods for unconstrained and constrained minimization using Fibonacci, gradient, conjugate gradient, Fletcher-Powell methods and penalty function approach. Classical optimization--Lagrange multiplier, Kuhn-Tucker conditions. Emphasis is on developing efficient digital computer algorithms for design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 812 Mathematical Program Engineering Design 3.0 Credits

Approximation theory projection theorem. Solution of nonlinear equations by Newton-Raphson method. Resource allocation, linear programming, and network flow problems. Integer programming for digital filter design and power system expansion problems. Gamory's algorithm.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 813 Computer-Aided Network Design 3.0 Credits

Simulation and circuit analysis programs: PCAP, MIMIC, GASP. Data structures. Algorithms. Languages. Interactive I/O. Integration of subroutines for simulation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 817 Non-Linear Control Systems 3.0 Credits

Covers key topics of feedback linearization, sliding mode control, model reference adaptive control, self-tuning controllers and on-line parameter estimation. In addition additional no n-linear topics such as Barbalat’s Lemma, Kalman-Yakubovich Lemma, passivity, absolute stability, and establishing boundedness of signals are presented. The focus of the course is the understanding each of these algorithms in detail through derivation and their implementation through coding in Matlab and Simulink.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 513 [Min Grade: C]

ECES 818 Machine Learning & Adaptive Control 3.0 Credits

System identification and parameter estimation, gradient search, least squares and Neural Networks methods. Closed loop implementation of system learning and self-organizing controllers. Random searching learning systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 512 [Min Grade: C]

ECES 821 Reliable Communications & Coding I 3.0 Credits

Covers fundamentals of information theory, including measures of communication, channel capacity, coding for discrete sources, converse of coding system, noisy-channel coding, rate distortion theory for memoryless sources and for sources with memory, and universal coding.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 521 [Min Grade: C] and ECES 522 [Min Grade: C]

ECES 822 Reliable Communications & Coding II 3.0 Credits

Introduces algebra of coding, including groups, rings, fields, and vector fields. Covers finite fields, decoding circuitry, techniques for coding and decoding, linear codes, error-correction capabilities of linear codes, dual codes and weight distribution, important linear block codes, perfect codes, and Plotkin's and Varshamov's bounds.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 821 [Min Grade: C]

ECES 823 Reliable Communications & Coding III 3.0 Credits

Continues techniques for coding and decoding. Covers convolutional codes; Viterbi algorithm; BCH, cyclic, burst-error-correcting, Reed-Solomon, and Reed-Muller codes; and elements of cryptography.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 822 [Min Grade: C]

ECES 890 Advanced Special Topics in Systems Engineering 1.0-9.0 Credit

Covers advanced special topics of interest to students and faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 898 Master's Thesis in Systems Engineering 12.0 Credits

Master's thesis in systems engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 921 Reliable Communications & Coding I 3.0 Credits

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECES 997 Dissertation Research in Systems Engineering 1.0-12.0 Credit

Graded Ph.D. dissertation in systems engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECES 998 Ph.D. Dissertation in Systems Engineering 1.0-12.0 Credit

Ph.D. dissertation in systems engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

Electrical & Computer Engr Courses

ECE 501 Topics in Circuits and Systems 3.0 Credits

Circuit laws, transfer functions, convolution, transform techniques, systems engineering. This series of courses may be used to meet the admission prerequisites to ECE graduate program. One credit per term is creditable to the M.S.E.E. degree.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 502 Topics In Communications, Controls and Computers 3.0 Credits

Modulation theory, noise, feedback theory, stability, computer engineering fundamentals, computers in communication and controls. This series of courses may be used to meet the admission prerequisites to the ECE graduate program. One credit per term is creditable to the M.S.E.E. degree.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 503 Topics in Mathematical Techniques In Electrical and Computer Engineering 3.0 Credits

Complex variables in communication and control, matrix methods in circuits and systems, vector calculus in fields, two-dimensional image processing. This series of courses may be used to meet the admission prerequisites to the ECE graduate program. One credit per term is creditable to the M.S.E.E. degree.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 571 Introduction to Electrical and Computer Engineering Research 0.0 Credits

Topics of departmental research. Thesis selection. Required of all full-time graduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 572 Techniques of Electrical and Computer Engineering Research 0.0 Credits

Techniques for making technical presentations: oral and written modes. Meeting organization, audience awareness. Writer-to-reader communication. Required of all full-time graduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 573 Presentation of Electrical and Computer Engineering Research 0.0 Credits

Conference attendance and critique. Student presentation and critique. Topics of concern: professional ethics, liability, etc. Required of all full-time graduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

Electrical Engineering Lab Courses

Electrical and Computer Engineering Faculty

Fernand Cohen, PhD (Brown University). Professor. Surface modeling; tissue characterization and modeling; face modeling; recognition and tracking.
Kapil Dandekar, PhD (University of Texas-Austin) Director of the Drexel Wireless Systems Laboratory (DWSL); Associate Dean of Research, College of Engineering. Professor. Cellular/mobile communications and wireless LAN; smart antenna/MIMO for wireless communications; applied computational electromagnetics; microwave antenna and receiver development; free space optical communication; ultrasonic communication; sensor networks for homeland security; ultrawideband communication.
Afshin Daryoush, ScD (Drexel University). Professor. Digital and microwave photonics; nonlinear microwave circuits; RFIC; medical imaging.
Bruce A. Eisenstein, PhD (University of Pennsylvania) Interim Dean, College of Engineering. Professor. Pattern recognition; estimation; decision theory.
Adam K. Fontecchio, PhD (Brown University) Electrical and Computer Engineering. Professor. Electro-optics; remote sensing; active optical elements; liquid crystal devices.
Gary Friedman, PhD (University of Maryland-College Park). Professor. Biological and biomedical applications of nanoscale magnetic systems.
Eli Fromm, PhD (Jefferson Medical College) Roy A. Brothers University Professor / Director for Center of Educational Research. Professor. Engineering education; academic research policy; bioinstrumentation; physiologic systems.
Edwin L. Gerber, PhD (University of Pennsylvania) Assistant Department Head for Evening Programs. Professor. Computerized instruments and measurements; undergraduate engineering education.
Allon Guez, PhD (University of Florida). Professor. Intelligent control systems; robotics, biomedical, automation and manufacturing; business systems engineering.
Mark Hempstead, PhD (Harvard University) Junior Colehower Chair. Assistant Professor. Computer engineering; power-aware computing; computer architecture; low power VLSI Design; wireless sensor networks.
Peter R. Herczfeld, PhD (University of Minnesota) Lester A. Kraus Professor/Director, Center for Microwave/Lightwave Engineering. Professor. Lightwave technology; microwaves; millimeter waves; fiberoptic and integrated optic devices.
Leonid Hrebien, PhD (Drexel University) Graduate Advisor and Assistant Department Head for Graduate Affairs. Professor. Tissue excitability; acceleration effects on physiology; bioinformatics.
Paul R. Kalata, PhD (Illinois Institute of Technology). Associate Professor. Stochastic and adaptive control theory; identification and decision theory; Kalman filters.
Moshe Kam, PhD (Drexel University) Robert G. Quinn Professor of Electrical and Computer Engineering and Department Head. Professor. Decision fusion and sensor fusion; mobile robots (especially robot navigation); pattern recognition (especially in handwriting applications); optimization and control.
Nagarajan Kandasamy, PhD (University of Michigan). Associate Professor. Embedded systems, self-managing systems, reliable and fault-tolerant computing, distributed systems, computer architecture, and testing and verification of digital systems.
Bruce Katz, PhD (University of Illinois). Adjunct Professor. Speech communication and computer science; artificial intelligence.
Youngmoo Kim, PhD (MIT). Associate Professor. Audio and music signal processing, voice analysis and synthesis, music information retrieval, machine learning.
Timothy P. Kurzweg, PhD (University of Pittsburgh). Associate Professor. Optical MEM modeling and simulation; system-level simulation; computer architecture.
Karen Miu, PhD (Cornell University). Professor. Power systems; distribution networks; distribution automation; optimization; system analysis.
Bahram Nabet, PhD (University of Washington) Associate Dean for Special Projects, College of Engineering; Electrical and Computer Engineering. Professor. Optoelectronics; fabrication and modeling; fiber optic devices; nanoelectronics; nanowires.
Prawat Nagvajara, Ph.D. (Boston University). Associate Professor. System on a chip; embedded systems; power grid computation; testing of computer hardware; fault-tolerant computing; VLSI systems; error control coding.
Dagmar Niebur, Ph.D. (Swiss Federal Institute of Technology). Associate Professor. Intelligent systems; dynamical systems; power system monitoring and control.
Chika Nwankpa, PhD (Illinois Institute of Technology). Professor. Power system dynamics; power electronic switching systems; optically controlled high power switches.
Karkal S. Prahbu, PhD (Harvard University). Auxiliary Professor. Computer and software engineering; advanced microprocessors and distributed operating systems.
Gail L. Rosen, PhD (Georgia Institute of Technology). Associate Professor. Signal processing, signal processing for biological analysis and modeling, bio-inspired designs, source localization and tracking.
Kevin J. Scoles, PhD (Dartmouth College) Associate Dean, College of Engineering, Office of Student Services. Associate Professor. Microelectronics; electric vehicles; solar energy; biomedical electronics.
Harish Sethu, PhD (Lehigh University). Associate Professor. Protocols, architectures and algorithms in computer networks; computer security; mobile ad hoc networks; large-scale complex adaptive networks and systems.
P. Mohana Shankar, PhD (Indian Institute of Technology) Allen Rothwarf Professor of Electrical and Computer Engineering. Professor. Wireless communications; biomedical ultrasonics; fiberoptic bio-sensors.
Baris Taskin, PhD (University of Pittsburgh). Associate Professor. Electronic design automation (EDA) of integrated circuits, high-performance VLSI circuits and systems, sequential circuit timing and synchronization, system-on-chip (SOC) design, operational research, VLSI computer-aided design.
Lazar Trachtenberg, DSc (Israel Institute of Technology). Professor. Fault tolerance; multi-level logic synthesis; signal processing; suboptimal filtering.
Oleh Tretiak, ScD (MIT) Robert C. Disque Professor of Electrical and Computer Engineering. Professor. Image processing; tomography; image registration; pattern recognition.
John MacLaren Walsh, PhD (Cornell University). Assistant Professor. Performance and convergence of belief/expectation propagation and turbo decoding/equalization/synchronization, permeation models for ion channels, composite adaptive systems theory.
Steven Weber, PhD (University of Texas-Austin) Assistant Department Head for Graduate Affairs, Electrical and Computer Engineering. Associate Professor. Mathematical modeling of computer and communication networks, specifically streaming multimedia and ad hoc networks.
Jaudelice Cavalcante de Oliveira, PhD (Georgia Institute of Technology). Associate Professor. Next generation Internet; quality of service in computer communication networks; wireless networks.

Interdepartmental Faculty

Dov Jaron, PhD (University of Pennsylvania) Calhoun Distinguished Professor of Engineering in Medicine. Professor. Mathematical, computer and electromechanical simulations of the cardiovascular system.
Jeremy R. Johnson, PhD (Ohio State University). Professor. Computer algebra; parallel computations; algebraic algorithms; scientific computing.
John Lacontora, PhD (New Jersey Institute of Technology). Associate Research Professor. Service engineering; industrial engineering.
Ryszard Lec, PhD (University of Warsaw Engineering College). Professor. Biomedical applications of visoelastic, acoustoptic and ultrasonic properties of liquid and solid media.
Spiros Mancoridis, PhD (University of Toronto) Interim Department Head, Computer Science. Professor. Software engineering; software security; code analysis; evolutionary computation.
Karen Moxon, PhD (University of Colorado). Associate Professor. Cortico-thalamic interactions; neurobiological perspectives on design of humanoid robots.
Paul Y. Oh, PhD (Columbia University) Associate Department Head for External Affairs, Department of Mechanical Engineering and Mechanics. Professor. Smart sensors servomechanisms; machine vision and embedded microcomputers for robotics and mechatronics.
Banu Onaral, Ph.D. (University of Pennsylvania) H.H. Sun Professor / Director, School of Biomedical Engineering Science and Health Systems. Professor. Biomedical signal processing; complexity and scaling in biomedical signals and systems.
Kambiz Pourrezaei, PhD (Rensselaer Polytechnic University). Professor. Thin film technology; nanotechnology; near infrared imaging; power electronics.
William C. Regli, PhD (University of Maryland-College Park). Professor. Artificial intelligence; computer graphics; engineering design and Internet computing.
Arye Rosen, PhD (Drexel University) Biomedical Engineering and Electrical Engineering. Microwave components and subsystems; utilization of RF/microwaves and lasers in therapeutic medicine.
Jonathan E. Spanier, PhD (Columbia University). Associate Professor. Electronic, ferroic and plasmonic nanostructures and thin-film materials and interfaces; scanning probe microscopy; laser spectroscopy, including Raman scattering.
Aydin Tozeren, PhD (Columbia University) Distinguished Professor and Director, Center for Integrated Bioinformatics, School of Biomedical Engineering, Science & Health Systems. Professor. Breast cell adhesion and communication, signal transduction networks in cancer and epithelial cells; integrated bioinformatics, molecular profiling, 3D-tumors, bioimaging.
Aspasia Zerva, PhD (University of Illinois). Professor. Earthquake engineering; mechanics; seismicity; probabilistic analysis.

Emeritus Faculty

Richard L. Coren, PhD (Polytechnic Institute of Brooklyn). Professor Emeritus. Electromagnetic fields, antennas, shielding, RFI, cybernetics of evolving systems.
Robert Fischl, PhD (University of Michigan) John Jarem Professor Emeritus / Director, Center for Electric Power Engineering. Professor Emeritus. Power: systems, networks, controls, computer-aided design, power systems, solar energy.
Vernon L. Newhouse, PhD (University of Leeds) Disque Professor Emeritus. Professor Emeritus. Biomedical and electrophysics: ultrasonic flow measurement, imaging and texture analysis in medicine, ultrasonic nondestructive testing and robot sensing, clinical engineering.
Hun H. Sun, PhD (Cornell University) Ernest O. Lange Professor Emeritus. Professor Emeritus. Systems and signals in biomedical control systems.
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