Computer Engineering

Bachelor of Science in Computer Engineering (BSCE): 192.0 quarter credits

About the Program

The major provides a broad focus on digital circuit design, computer hardware and organization, programming and computer software, algorithms, and networks. 

Computer engineers design smaller, faster, and more reliable computers and digital systems, embed microprocessors in larger systems (e.g., anti-lock brake systems), work in theoretical issues in computing, use object-oriented programming languages, and design large-scale software systems and computer networks. Computer engineers may work in positions that apply computers in control systems, digital signal processing, telecommunications, and power systems, and may design very large-scale integration (VLSI) integrated circuits and systems.

The computer engineering degree program is designed to provide our students with breadth in engineering, the sciences, mathematics, and the humanities, as well as depth in both software and hardware disciplines appropriate for a computer engineer. It embodies the philosophy and style of the Drexel Engineering Curriculum, and will develop the student's design and analytical skills. In combination with the co-op experience, it opens to the student opportunities in engineering practice, advanced training in engineering or in other professions, and an entry to business and administration.

The computer engineering program's courses in ECE are supplemented with courses from the departments of Mathematics and Computer Science. Students gain the depth of knowledge of computer hardware and software essential for the computer engineer.

Mission Statement

The ECE Department at Drexel University serves the public and the university community by providing superior career-integrated education in electrical and computer engineering; by conducting research in these fields, to generate new knowledge and technologies; and by promoting among all its constituents professionalism, social responsibility, civic engagement and leadership.

Program Educational Objectives

The Electrical and Computer Engineering Program Educational Objectives are such that its alumni, in their early years after graduation can:

1. Secure positions and continue as valued, creative, dependable, and proficient employees in a wide variety of fields and industries, in particular as electrical and computer engineers;

2. Succeed in graduate and professional studies, such as engineering, science, law, medicine and business;

3. Pursue professional development through lifelong learning opportunities for a successful and rewarding career;

4. Provide leadership in their profession, in their communities, and in the global society;

5. Contribute to their professional disciplines body of knowledge;

6. Function as responsible members of society with an awareness of the social and ethical ramifications of their work.

Student Outcomes

The department’s student outcomes reflect the skills and abilities that the curriculum is designed to provide to students by the time they graduate. These are:   

a)  an ability to apply knowledge of mathematics, science, and engineering;

b)  an ability to design and conduct experiments, as well as to analyze and interpret data;

c)  an ability to design a system, component, or process to meet desired needs within realistic constraints such as             economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability;

d)  an ability to function on multidisciplinary teams;

e)  an ability to identify, formulate, and solve engineering problems;

f)  an understanding of professional and ethical responsibility;

g) an ability to communicate effectively;

h) the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context;

i)  a recognition of the need for, and an ability to engage in life-long learning;

j)  a knowledge of contemporary issues;

k) an ability to use the techniques, skills, and modern engineering tools necessary for computer engineering practice.

Additional Information

The Computer Engineering program is accredited by the Engineering Accreditation Commission of ABET.

Additional information about the major is available on the ECE Department website.

Timothy P. Kurzweg, PhD
Associate Professor
Associate Department Head for Undergraduate Studies
Department of Electrical and Computer Engineering
Bossone Research Center, Suite 313
 

Amy Ruymann, MS
Associate Director – Undergraduate Advising
Department of Electrical and Computer Engineering
Bossone Research Center Suite 313
advising@ece.drexel.edu

To make an appointment, please call 215.895.2241
Drop-in hours: Mon - Fri 1:30 - 2:30.

Degree Requirements

General Education/Liberal Studies Requirements
ENGL 101Composition and Rhetoric I: Inquiry and Exploratory Research3.0
ENGL 102Composition and Rhetoric II: The Craft of Persuasion3.0
ENGL 103Composition and Rhetoric III: Thematic Analysis Across Genres3.0
PHIL 315Engineering Ethics3.0
UNIV E101The Drexel Experience2.0
General Education Requirements *18.0
Foundation Requirements
MATH 121Calculus I4.0
MATH 122Calculus II4.0
MATH 200Multivariate Calculus4.0
PHYS 101Fundamentals of Physics I4.0
PHYS 102Fundamentals of Physics II4.0
PHYS 201Fundamentals of Physics III4.0
CHEM 101General Chemistry I3.5
CHEM 102General Chemistry II4.5
BIO 141Essential Biology4.5
ENGR 121Computation Lab I2.0
ENGR 122Computation Lab II1.0
ECE 200Digital Logic Design3.0
ECE 201Foundations of Electric Circuits3.0
ECE 203Programming for Engineers3.0
ENGR 100Beginning Computer Aided Drafting for Design1.0
ENGR 101Engineering Design Laboratory I2.0
ENGR 102Engineering Design Laboratory II2.0
ENGR 103Engineering Design Laboratory III2.0
ENGR 201Evaluation & Presentation of Experimental Data I3.0
ENGR 202Evaluation & Presentation of Experimental Data II3.0
ENGR 220Fundamentals of Materials4.0
ENGR 231Linear Engineering Systems3.0
ENGR 232Dynamic Engineering Systems3.0
Professional Requirements
CS 260Data Structures3.0
CS 265Advanced Programming Tools and Techniques3.0
ECE 391Introduction to Engineering Design Methods1.0
ECE 491 [WI] Senior Design Project I2.0
ECE 492 [WI] Senior Design Project II2.0
ECE 493Senior Design Project III4.0
ECEC 301Advanced Programming for Engineers3.0
ECEC 302Digital Systems Projects4.0
ECEC 304Design with Microcontrollers4.0
ECEC 353Systems Programming3.0
ECEC 355Computer Organization & Architecture4.0
ECEC 356Embedded Systems4.0
ECEC 357Introduction to Computer Networks4.0
ECEL 301 [WI] Electrical Engineering Laboratory2.0
ECEL 302ECE Laboratory II2.0
ECEL 303ECE Laboratory III2.0
ECEL 304ECE Laboratory IV2.0
MATH 221Discrete Mathematics3.0
ECES 301Transform Methods and Filtering 4.0
ECE 361Probability for Engineers3.0
or ECE 362 Engineering Statistics
or ENGR 361 Statistical Analysis of Engineering Systems
Six Computer Engineering Courses 18.0
Free Electives11.5
Total Credits192.0

*

General Education Requirements.


Writing-Intensive Course Requirements

In order to graduate, all students must pass three writing-intensive courses after their freshman year. Two writing-intensive courses must be in a student's major. The third can be in any discipline. Students are advised to take one writing-intensive class each year, beginning with the sophomore year, and to avoid “clustering” these courses near the end of their matriculation. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.

A "WI" next to a course in this catalog may indicate that this course can fulfill a writing-intensive requirement. For the most up-to-date list of writing-intensive courses being offered, students should check the Writing Intensive Course List at the University Writing Center. Students scheduling their courses can also conduct a search for courses with the attribute "WI" to bring up a list of all writing-intensive courses available that term. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.

Sample Plan of Study

 

5 YR Ug Co-op Concentration

Term 1Credits
CHEM 101General Chemistry I3.5
COOP 101Career Management and Professional Development0.0
ENGL 101Composition and Rhetoric I: Inquiry and Exploratory Research3.0
ENGR 100Beginning Computer Aided Drafting for Design1.0
ENGR 101Engineering Design Laboratory I2.0
MATH 121Calculus I4.0
UNIV E101The Drexel Experience1.0
ENGR 121Computation Lab I2.0
 Term Credits16.5
Term 2
CHEM 102General Chemistry II4.5
ENGL 102Composition and Rhetoric II: The Craft of Persuasion3.0
ENGR 102Engineering Design Laboratory II2.0
ENGR 122Computation Lab II1.0
MATH 122Calculus II4.0
PHYS 101Fundamentals of Physics I4.0
UNIV E101The Drexel Experience0.5
 Term Credits19.0
Term 3
BIO 141Essential Biology4.5
ENGL 103Composition and Rhetoric III: Thematic Analysis Across Genres3.0
ENGR 103Engineering Design Laboratory III2.0
MATH 200Multivariate Calculus4.0
PHYS 102Fundamentals of Physics II4.0
UNIV E101The Drexel Experience0.5
 Term Credits18.0
Term 4
ECE 200Digital Logic Design3.0
ENGR 201Evaluation & Presentation of Experimental Data I3.0
ENGR 220Fundamentals of Materials4.0
ENGR 231Linear Engineering Systems3.0
PHYS 201Fundamentals of Physics III4.0
 Term Credits17.0
Term 5
ECE 201Foundations of Electric Circuits3.0
ECE 203Programming for Engineers3.0
ENGR 202Evaluation & Presentation of Experimental Data II3.0
ENGR 232Dynamic Engineering Systems3.0
MATH 221Discrete Mathematics3.0
 Term Credits15.0
Term 6
ECEC 301Advanced Programming for Engineers3.0
ECEC 302Digital Systems Projects4.0
ECEL 301 [WI] Electrical Engineering Laboratory2.0
ECES 301Transform Methods and Filtering 4.0
General Education elective*3.0
 Term Credits16.0
Term 7
ECEC 304Design with Microcontrollers4.0
ECEC 355Computer Organization & Architecture4.0
ECEL 302ECE Laboratory II2.0
PHIL 315Engineering Ethics3.0
Free elective 3.0
 Term Credits16.0
Term 8
CS 265Advanced Programming Tools and Techniques3.0
ECEC 357Introduction to Computer Networks4.0
ECEL 303ECE Laboratory III2.0
General Education elective*3.0
 Term Credits12.0
Term 9
CS 260Data Structures3.0
ECE 391Introduction to Engineering Design Methods (Also offered spring term.)1.0
ECEC 356Embedded Systems4.0
ECEC 353Systems Programming3.0
ECEL 304ECE Laboratory IV2.0
ECE 361, 362,
or ENGR 361
Probability for Engineers
Engineering Statistics
Statistical Analysis of Engineering Systems
3.0
General Education elective*3.0
 Term Credits19.0
Term 10
ECE 491 [WI] Senior Design Project I2.0
Two Computer Engineering electives 6.0
General Education elective*3.0
Free Elective 3.0
 Term Credits14.0
Term 11
ECE 492 [WI] Senior Design Project II2.0
Two Computer Engineering electives 6.0
General Education elective*3.0
Free elective 3.5
 Term Credits14.5
Term 12
ECE 493Senior Design Project III4.0
Two Computer Engineering electives 6.0
General Education elective*2.0
Free elective 3.0
 Term Credits15.0
Total Credit: 192.0

*

 See degree requirements.


Co-op/Career Opportunities

Drexel University's co-op program has an 80 year history and is one of the oldest and largest co-op programs in the world. Students graduate with 6-18 months of full time employment experience, depending on their choice of a 4-year or 5-year program. The majority of Computer Engineering students in ECE choose the 5-year program and graduate with 18 months of full-time work experience, and often receive a job offer from their third co-op employer or from a connection made from one of their co-op experiences.

Computer engineers work for computer and microprocessor manufacturers; manufacturers of digital devices for telecommunications, peripherals, electronics, control, and robotics; software engineering; the computer network industry; and related fields. A degree in computer engineering can also serve as an excellent foundation to pursue graduate professional careers in medicine, law, business, and government.

Graduates are also pursuing advanced studies in electrical and computer engineering, aerospace engineering, and mechanical engineering at such schools as MIT, Stanford, Princeton, Georgia Institute of Technology, University of California at Berkeley, University of Pennsylvania, and University of Maryland.

The Steinbright Career Development Center had a co-op placement rate of approximately 99% for electrical and computer engineering majors.

Co-op employers for computer engineering majors include:

  • Comcast Corporation
  • Independence Blue Cross
  • Lockheed Martin
  • Micron Technology, Inc
  • National Board of Medical Examiners
  • PJM Interconnection, LLC
  • SAP America
  • Susquehanna International Group LLC
  • UNISYS Corporation
  • Woodward McCoach, Inc.
  • Amazon, Inc.
  • Microsoft's Explore Internship Program
  • South Korea KAIST Hubo lab

For more information about the co-op process, please contact the Steinbright Career Development Center.

Dual/Accelerated Degree

Accelerated Program

The accelerated programs of the College of Engineering provide opportunities for highly talented and strongly motivated students to progress toward their educational goals essentially at their own pace. These options include opportunities for accelerated studies, dual degrees, and combined bachelor's/master's programs.

Primarily through advanced placement, credit by examination, flexibility of scheduling, and independent study, the "fast track" makes it possible to complete the undergraduate curriculum and initiate graduate study in less than the five years required by the standard curriculum.

Dual Degree Bachelor's Programs

With careful planning, students can complete both a Computer Engineering and an Electrical Engineering degree in the time usually required to complete one degree. For detailed information the student should contact the ECE advisor.

Bachelor's/Master's Dual Degree Program

Exceptional students can also pursue a master of science degree in the same period as the bachelor of science.

For more information on these and other options, visit the Department of Electrical and Computer Engineering BS/MS page.

Minor in Computer Engineering

The computer engineering minor is designed to provide students from other computer-intensive majors—such as computer science or other engineering majors—with a foundation of knowledge in the hardware portion of computer systems. The minor consists of a minimum of seven ECE courses. There are four required courses and an additional 12.0 credits of elective courses. Students majoring in Electrical Engineering and minoring in Computer Engineering may only choose CE minor electives from the ECEC courses.

Prerequisites

The minor assumes that students will have a background in mathematics, physics, and computer programming equivalent to that covered in the first two years of engineering.

Calculus prerequisites should include MATH 121, MATH 122 and MATH 200. Physics requirements are PHYS 101PHYS 102 and PHYS 201. Programming experience must include CS 121/CS 122/ CS 123 or ENGR 121/ENGR 122 or CS 171 at the minimum. CS 172, CS 260 and CS 265 are also recommended, and are required for some upper level ECEC courses. Courses taken to meet these requirements will not count toward the minor.  

Required Courses
ECE 200Digital Logic Design3.0
ECEC 302Digital Systems Projects4.0
ECEC 355Computer Organization & Architecture4.0
ECEL 304ECE Laboratory IV (prerequisite waived for minor)2.0
Electives *12.0
Total Credits25.0

*

Students should choose an additional 12 credits from 300- and/or 400-level Computer Engineering (ECEC) courses. All prerequisites must be satisfied.


Additional Information

Additional information about this minor is available on the ECE Department website.

Timothy  P. Kurzweg, PhD
Associate Professor
Associate Department Head for Undergraduate Studies
Department of Electrical and Computer Engineering
Bossone Research Center, Suite 313
3120-40 Market Street
advising@ece.drexel.edu

Amy Ruymann, MS
Associate Director – Undergraduate Advising
Department of Electrical and Computer Engineering
Bossone Research Center, Suite 313
advising@ece.drexel.edu

To make an appointment, please call 215.895.2241
Drop-in hours: Mon - Fri 1:30 - 2:30

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

Adaptive Signal Processing and Information Theory Research Group

The Adaptive Signal Processing and Information Theory Research Group conducts research in the area of signal processing and information theory. Our main interests are belief/expectation propagation, turbo decoding and composite adaptive system theory. We are currently doing projects on the following topics:
i) Delay mitigating codes for network coded systems,
ii) Distributed estimation in sensor networks via expectation propagation,
iii) Turbo speaker identification,
iv) Performance and convergence of expectation propagation,
v) Investigating bounds for SINR performance of autocorrelation based channel shorteners.

Applied Networking Research Lab

Applied Networking Research Lab (ANRL) projects focus on modeling and simulation as well as experimentation in wired, wireless and sensor networks. ANRL is the home of MuTANT, a Multi-Protocol Label Switched Traffic Engineering and Analysis Testbed composed of 10 high-end Cisco routers and several PC-routers, also used to study other protocols in data networks as well as automated network configuration and management. The lab also houses a sensor network testbed.

Bioimage Laboratory

Uses computer gaming hardware for enhanced and affordable 3-D visualization, along with techniques from information theory and machine learning to combine the exquisite capabilities of the human visual system with computational sensing techniques for analyzing vast quantities of image sequence data.

Data Fusion Laboratory

The Data Fusion Laboratory investigates problems in multisensory detection and estimation, with applications in robotics, digital communications, radar, and target tracking. Among the projects in progress: computationally efficient parallel distributed detection architectures, data fusion for robot navigation, modulation recognition and RF scene analysis in time-varying environments, pattern recognition in biological data sequences and large arrays, and hardware realizations of data fusion architectures for target detection and target tracking.

Drexel Network Modeling Laboratory

The Drexel Network Modeling Laboratory investigates problems in the mathematical modeling of communication networks, with specific focus on wireless ad hoc networks, wireless sensor networks, and supporting guaranteed delivery service models on best effort and multipath routed networks. Typical methodologies employed in our research include mathematical modeling, computer simulation, and performance optimization, often with the end goal of obtaining meaningful insights into network design principles and fundamental performance tradeoffs.

Drexel Power-Aware Computing Laboratory

The Power-Aware Computing Lab investigates methods to increase energy efficiency across the boundaries of circuits, architecture, and systems. Our recent accomplishments include the Sigil profiling tool, scalable modeling infrastructure for accelerator implementations, microarchitecture-aware VDD gating algorithms, an accelerator architecture for ultrasound imaging, evaluation of hardware reference counting, hardware and operating system support for power-agile computing, and memory systems for accelerator-based architectures.

Drexel University Nuclear Engineering Education Laboratory

The field of nuclear engineering encompasses a wide spectrum of occupations, including nuclear reactor design, medical imaging, homeland security, and oil exploration. The Drexel University Nuclear Engineering Education Laboratory (DUNEEL) provides fundamental hands on understanding for power plant design and radiation detection and analysis. Software based study for power plant design, as well as physical laboratory equipment for radiation detection, strengthen the underlying concepts used in nuclear engineering such that the student will comprehend and appreciate the basic concepts and terminology used in various nuclear engineering professions. Additionally, students use the laboratory to develop methods for delivering remote, live time radiation detection and analysis. The goal of DUNEEL is to prepare students for potential employment in the nuclear engineering arena. 

Drexel VLSI Laboratory

The Drexel VLSI Laboratory investigates problems in the design, analysis, optimization and manufacturing of high performance (low power, high throughput) integrated circuits in contemporary CMOS and emerging technologies. Suited with industrial design tools for integrated circuits, simulation tools and measurement beds, the VLSI group is involved with digital and mixed-signal circuit design to verify the functionality of the discovered novel circuit and physical design principles. The Drexel VLSI laboratory develops design methodologies and automation tools in these areas, particularly in novel clocking techniques, featuring resonant clocking, and interconnects, featuring wireless interconnects.

Drexel Wireless Systems Laboratory

The Drexel Wireless Systems Laboratory (DWSL) contains an extensive suite of equipment for constructing, debugging, and testing prototype wireless communications systems. Major equipment within DWSL includes:

  • three software defined radio network testbeds (HYDRA, USRP, and WARP) for rapidly prototyping radio, optical and ultrasonic communications systems,
  • a TDK RF anechoic chamber and EMSCAN desktop antenna pattern measurement system,
  • a materials printer and printed circuit board milling machine for fabricating conformal antennas and
  • wireless protocol conformance testing equipment from Aeroflex.

The lab is also equipped with network analyzers, high speed signal generators, oscilloscopes, and spectrum analyzers as well as several Zigbee development platforms for rapidly prototyping sensor networks.

DWSL personnel also collaborate to create wearable, fabric based transceivers through collaboration with the Shima Seiki Haute Laboratory in the Drexel ExCITe Center. The knitting equipment at Drexel includes sixteen SDS-ONE APEX3 workstations and four state-of-the-art knitting machines. The workstations accurately simulate fabric construction and provide researchers and designers the opportunity to program, create and simulate textile prototypes, import CAD specifications of final products, and produce made-to-measure or mass-produced pieces on Shima Seiki knitting machines. For testing smart textiles for biomedical, DWSL personnel also have collaborators in the Center for Interdisciplinary Clinical Simulation and Practice (CICSP) in the Drexel College of Medicine which provides access to medical mannequin simulators.

Ecological and Evolutionary Signal-processing and Informatics Laboratory

The Ecological and Evolutionary Signal-processing and Informatics Laboratory (EESI) seeks to solve problems in high-throughput genomics and engineer better solutions for biochemical applications. The lab's primary thrust is to enhance the use of high-throughput DNA sequencing technologies with pattern recognition and signal processing techniques. Applications include assessing the organism content of an environmental sample, recognizing/classifying potential and functional genes, inferring environmental factors and inter-species relationships, and inferring microbial evolutionary relationships from short-read DNA/RNA fragments. The lab also investigates higher-level biological systems such as modeling and controlling chemotaxis, the movement of cells.

Electric Power Engineering Center

This newly established facility makes possible state-of-the-art research in a wide variety of areas, ranging from detailed theoretical model study to experimental investigation in its high voltage laboratories. The mission is to advance and apply scientific and engineering knowledge associated with the generation, transmission, distribution, use, and conservation of electric power. In pursuing these goals, this center works with electric utilities, state and federal agencies, private industries, nonprofit organizations and other universities on a wide spectrum of projects. Research efforts, both theoretical and experimental, focus on the solution of those problems currently faced by the electric power industry. Advanced concepts for electric power generation are also under investigation to ensure that electric power needs will be met at the present and in the future.

Electronic Design Automation Facility

Industrial-grade electronic design automation software suite and intergrated design environment for digital, analog and mixed-signal systems development. Field Programmable Gate Array (FPGA) development hardware. Most up-to-date FPGA/embedded system development hardware kits. Printed circuit board production facility. Also see Drexel VLSI Laboratory.

Microwave-Photonics Device Laboratories

The laboratory is equipped with test and measurement equipment for high-speed analog and digital electronics and fiber optic systems. The test equipment includes network analyzers from Agilent (100kHz- 1.3 GHz and 45 Mhz-40 GHz), and Anritsu (45 MHz-6 GHz); spectrum analyzers from Tektronix, HP, and Agilent with measurement capability of DC to 40 GHz and up to 90 GHz using external mixers; signal generators and communication channel modulators from HP, Rhode-Schwartz, Systron Donner, and Agilent; microwave power meter and sensor heads, assortment of passive and active microwave components up to 40 GHz ; data pattern generator and BER tester up to 3Gb/s; optical spectrum analyzer from Anritsu and power meters from HP; single and multimode fiber optic based optical transmitter and receiver boards covering ITU channels at data rates up to 10Gb/s; passive optical components such as isolator, filter, couplers, optical connectors and fusion splicer; LPKF milling machine for fabrication of printed circuit boards; wire-bonding and Cascade probe stations; Intercontinental test fixtures for testing of MMIC circuits and solid-state transistors; state-of-the-art microwave and electromagnetic CAD packages such as Agilent ADS, ANSYS HFSS, and COMSOL multi-physics module.

Music and Entertainment Technology Laboratory

The Music and Entertainment Technology Laboratory (MET-lab) is devoted to research in digital media technologies that will shape the future of entertainment, especially in the areas of sound and music. We employ digital signal processing and machine learning to pursue novel applications in music information retrieval, music production and processing technology, and new music interfaces. The MET-lab is also heavily involved in outreach programs for K-12 students and hosts the Summer Music Technology program, a one-week learning experience for high school students. Lab facilities include a sound isolation booth for audio and music recording, a digital audio workstation running ProTools, two large multi-touch display interfaces of our own design, and a small computing cluster for distributed processing.

NanoPhotonics+ Lab

Our research is primarily in the area of nanophotonics with a focus on the nanoscale interaction of light with matter. Interests include: liquid crystal/polymer composites for gratings, lenses and HOEs; liquid crystal interactions with surfaces and in confined nanospaces; alternative energy generation through novel photon interactions; ink-jet printed conducting materials for RF and photonic applications; and the creation and development of smart textiles technologies including soft interconnects, sensors, and wireless implementations.

Opto-Electro-Mechanical Laboratory

This lab concentrates on the system integration on optics, electronics, and mechanical components and systems, for applications in imaging, communication, and biomedical research. Research areas include: Programmable Imaging with Optical Micro-electrical-mechanical systems (MEMS), in which microscopic mirrors are used to image light into a single photodetector; Pre-Cancerous Detection using White Light Spectroscopy, which performs a cellular size analysis of nuclei in tissue; Free-space Optical Communication using Space Time Coding, which consists of diffused light for computer-to-computer communications, and also tiny lasers and detectors for chip-to-chip communication; Magnetic Particle Locomotion, which showed that particles could swim in a uniform field; and Transparent Antennas using Polymer, which enables antennas to be printed through an ink-jet printer.

Plasma and Magnetics Laboratory

Research is focused on applications of electrical and magnetic technologies to biology and medicine. This includes the subjects of non-thermal atmospheric pressure plasma for medicine, magnetic manipulation of particles for drug delivery and bio-separation, development of miniature NMR sensors for cellular imaging and carbon nanotube cellular probes.

Power Electronics Research Laboratory

The Power Electronics Research Laboratory (PERL) is involved in circuit and design simulation, device modeling and simulation, and experimental testing and fabrication of power electronic circuits. The research and development activities include electrical terminations, power quality, solar photovoltaic systems, GTO modeling, protection and relay coordination, and solid-state circuit breakers. The analysis tools include EMPT, SPICE, and others, which have been modified to incorporate models of such controllable solid-state switches as SCRs, GTOs, and MOSFETs. These programs have a wide variety and range of modeling capabilities used to model electromagnetics and electromechanical transients ranging from microseconds to seconds in duration. The PERL is a fully equipped laboratory with 42 kVA AC and 70 kVA DC power sources and data acquisition systems, which have the ability to display and store data for detailed analysis. Some of the equipment available is a distribution and HV transformer and three phase rectifiers for power sources and digital oscilloscopes for data measuring and experimental analysis. Some of the recent studies performed by the PERL include static VAR compensators, power quality of motor controllers, solid-state circuit breakers, and power device modeling which have been supported by PECO, GE, Gould, and EPRI.

RE Touch Lab

The RE Touch Lab is investigating the perceptual and mechanical basis of active touch perception, or haptics, and the development of new technologies for stimulating the sense of touch, allowing people to touch, feel, and interact with digital content as seamlessly as we do with objects in the real world.  We study the scientific foundations of haptic perception and action, and the neuroscientific and biomechanical basis of touch, with a long-term goal of uncovering the fundamental perceptual and mechanical computations that enable haptic interaction. We also create new technologies for rendering artificial touch sensations that simulate those that are experienced when interacting with real objects, inspired by new findings on haptic perception. 

Testbed for Power-Performance Management of Enterprise Computing Systems

This computing testbed is used to validate techniques and algorithms aimed at managing the performance and power consumption of enterprise computing systems. The testbed comprises a rack of Dell 2950 and Dell 1950 PowerEdge servers, as well as assorted desktop machines, networked via a gigabit switch. Virtualization of this cluster is enabled by VMWare's ESX Server running the Linux RedHat kernel. It also comprises of a rack of ten Apple Xserve machines networked via a gigabit switch. These servers run the OS X Leopard operating systems and have access to a RAID with TBs of total disk capacity.

Elec & Comp Engr-Computers Courses

ECEC 301 Advanced Programming for Engineers 3.0 Credits

An advanced introduction to classes and objects; inheritance and polymorphism; abstract classes and interfaces; exception handling; files and streams; garbage collection and dynamic memory allocation; recursion; using linked lists, stacks, queues, and trees; search and sorting algorithms; generic methods and classes; a comparative introduction to dominant programming languages; engineering examples.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECE 203 [Min Grade: D] or CS 203 [Min Grade: D]

ECEC 302 Digital Systems Projects 4.0 Credits

Offers hands-on experiences in digital system design with automation tools. Uses field programmable gate arrays in the projects. Some or all pre-requisites may be taken as either a pre-requisite or co-requisite. Please see the department for more information.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: CS 171 [Min Grade: D] (Can be taken Concurrently) or ECE 203 [Min Grade: D] or CS 203 [Min Grade: D]) and ECE 200 [Min Grade: D]

ECEC 304 Design with Microcontrollers 4.0 Credits

Offers hands-on experience in the design of controllers that incorporate microcontrollers as an embedded component in a larger system. The microcomputer topics to be studied will include architecture, software, programming and interfaces.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECE 200 [Min Grade: D] and (CS 171 [Min Grade: D] or ECE 203 [Min Grade: D] or CS 203 [Min Grade: D])

ECEC 352 Secure Computer Systems: Design Concepts 4.0 Credits

Covers concepts of secure computation, including economics vs. faults, errors, and hidden messages; mathematical foundations of secure computing; design issues in fault-tolerant computing; and testability and cryptography.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEC 302 [Min Grade: D] and MATH 221 [Min Grade: D]

ECEC 353 Systems Programming 3.0 Credits

This course introduces computer systems, including interaction of hardware and software through the operating system, from the programmer's perspective. Three fundamental abstractions are emphasized: processes, virtual memory, and files. These abstractions provide programmers a common interface to a wide variety of hardware devices. Topics covered include linking, system level I/O, concurrent programming, and network programming.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: CS 265 [Min Grade: D]

ECEC 355 Computer Organization & Architecture 4.0 Credits

This course will cover the principles of designing microprocessors using solid engineering fundamentals and quantitative cost/performance trade-offs. Topics will cover instruction set architectures, arithmetic for computers, assessing and understanding processor performance, processor datapath and control, pipelining, cache design, and virtual-memory design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECE 200 [Min Grade: D] or CS 270 [Min Grade: D]) and ECEC 302 [Min Grade: D]

ECEC 356 Embedded Systems 4.0 Credits

Lectures will cover theoretical concepts of embedded and cyber‐physical systems including discrete and continuous dynamics, hybrid systems, state machines, concurrent computation, embedded systems architecture and scheduling. Lab involves programming embedded applications for the decentralized software services architecture using C# and the Microsoft Robotics Software Development Kit (SDK) together with the hardware image processing and tracking capabilities of the Kinect sensor.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 304 [Min Grade: D]

ECEC 357 Introduction to Computer Networks 4.0 Credits

History of the Internet; introduction to packet switching, circuit switching and virtual circuit switching; statistical multiplexing; protocol layering; metrics of network performance including bandwidth, delay and loss; medium access protocols and Ethernet; routing algorithms; end-to-end issues; flow and congestion control; an overview of application layer protocols.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECE 203 [Min Grade: D] or CS 171 [Min Grade: D]

ECEC 390 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

ECEC 411 Computer Hardware 3.0 Credits

Covers the design and performance of computer hardware devices, including direct memory access, priority arbitration, double buffering, and bus standards. Fall.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECEC 355 [Min Grade: D]

ECEC 412 Modern Processor Design 3.0 Credits

This course introduces modern processor design in a systematic manner. It discusses dynamically scheduled superscalar techniques including multi-issue, dynamic instruction scheduling, speculative execution, and branch prediction; advanced cache designs, and new techniques including SMT and VLIW. The course provides a comprehensive coverage of modern processor architectures.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 355 [Min Grade: D] or CS 281 [Min Grade: D]

ECEC 413 Introduction to Parallel Computer Architecture 3.0 Credits

This course provides an introduction to the fundamental principles and engineering trade-offs involved in designing modern parallel computers (multi-processors). Topics covered include, but are not limited to, shared-memory and message-passing programming, cache-coherence, synchronization, scalable distributed memory multi-processors, and interconnection techniques.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 355 [Min Grade: D] or CS 281 [Min Grade: D]

ECEC 414 High Performance Computing 3.0 Credits

This course is an introduction to high performance computing, including both concepts and applications. Course contents will include discussions of different types of high performance computer architectures (multi-core/multi-threaded processors, parallel computers, etc.), the design, implementation, optimization and analysis of efficient algorithms for uni-processors, multi-threaded processors, and parallel computers, and high performance programming.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 355 [Min Grade: D] or (CS 281 [Min Grade: D] and CS 282 [Min Grade: D])

ECEC 421 Introduction to Operating Systems I 3.0 Credits

Covers basic concepts of computer operating systems, including multiprocessing and multiprogramming systems, lock operations, synchronization, and file structures. Winter.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECEC 355 [Min Grade: D] and CS 260 [Min Grade: D]

ECEC 422 Introduction to Operating Systems I 3.0 Credits

Further develops the topics of ECEC 421. Spring.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEC 421 [Min Grade: D]

ECEC 431 Introduction to Computer Networks 3.0 Credits

Covers topics in computer and telecommunications network design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECE 200 [Min Grade: D] and CS 260 [Min Grade: D]

ECEC 432 Internet Architecture and Protocols 3.0 Credits

Covers architecture, protocols, and services of the Internet with an analytical approach focused on design principles; Internet architecture and topology; architecture of web and mail servers; router architectures; routing protocols; multicasting; multimedia over IP and associated protocols; Quality-of-Service issues in the Internet.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 357 [Min Grade: D] or CS 472 [Min Grade: D]

ECEC 433 Network Programming 3.0 Credits

Covers application layer protocol and how applications use the transport layer; principles and practice of network programming; the client-server model; concurrent processing; introduction to sockets and related functions client and server software design with examples; principles, issues and challenges in e-mail and web application protocols; security protocols; and network life system concepts.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 357 [Min Grade: D]

ECEC 441 Robotic Computer Interface & Control I 3.0 Credits

Covers fundamentals of robotics systems, including mechanics, actuators, sensors, kinematics, and inverse kinematics. Fall.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECES 356 [Min Grade: D]

ECEC 442 Robotic Computer Interface & Control II 3.0 Credits

Covers robot dynamics, Lagrangian and Newton Euler methods, linear control of robots, path planning, and computer implementation. Winter.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEC 441 [Min Grade: D]

ECEC 443 Robotic Computer Interface & Control III 3.0 Credits

Covers robot-computer interface methods, including redundancy, optimal control, robustness, nonlinear control, adaptive control, and multiprocessor control. Spring.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEC 442 [Min Grade: D]

ECEC 451 Computer Arithmetic 3.0 Credits

This course provides an introduction to number representations used in computer arithmetic, issues of complexity in arithmetic operations, fixed point arithmetic, floating point arithmetic, and residue number systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECE 200 [Min Grade: D] and ECEC 355 [Min Grade: D]

ECEC 453 Image Processing Architecture 3.0 Credits

This course covers applications of computing techniques and hardware in image (still and video) processing. Methods of compression (lossless, lossy), video compression, JPEG standards, MPEG standards, processing requirements, and implementations for multimedia.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECE 200 [Min Grade: D] and ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D]

ECEC 455 Intelligent System Architectures 3.0 Credits

This course outlines the principles of designing the architectures for intelligent systems. Methods of knowledge representation are compared for a variety of engineering problems. Methods of sensing and behavior generation are demonstrated for applications in large engineering and information systems including autonomous robots. Principles of goal-oriented computers are discussed, and modules of intelligent systems architectures are described. Theoretical fundamentals and practical techniques for learning are also covered.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: MATH 221 [Min Grade: D] and ECEC 355 [Min Grade: D]

ECEC 457 Security in Computing 3.0 Credits

The course introduces ideas from Cryptography and Fault Tolerant Computing. Cryptography studies how to artificially create distortions that being interwoven with computations mask them from eavesdropping. Fault Tolerance studies techniques of suppressing effects of natural noises that operate in computation channels. The course deals with both some introductory issues in Public Key Cryptography and some important aspects of designing Fault Tolerant Systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 355 [Min Grade: D]

ECEC 459 Testing of Hardware 3.0 Credits

Testing has become the largest expense item in the semiconductor industry. There is rapidly being developed new techniques in testing, design for test and built-in self-test because no existing set of techniques can satisfy the existing and future needs. The course reviews, in a unified way, important issues in testing and diagnosis of hardware. Together with the "Security in Computing" course, it brings a design engineer student to the state of the art level in the field.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 355 [Min Grade: D]

ECEC 471 Introduction to VLSI Design 3.0 Credits

This is an introductory course where systematic understanding, design and analysis of digital VLSI integrated circuits will be covered. The course will begin with a review of CMOS transistor operation and semiconductor processes. Logic design with CMOS transistor and circuit families will be described. Specifically, layout, design rules, and circuit simulation will be addressed. Performance metrics will be analyzed in design and simulation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECE 200 [Min Grade: D] or CS 270 [Min Grade: D]) and (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D])

ECEC 472 VLSI Design & Automation 3.0 Credits

Design and analysis of VLSI integrated circuits will be covered from circuits and systems design perspectives. First, system timing and arithmetic building blocks will be presented. Then, design automation will be presented by hierarchical design examples using hardware description languages (HDL) and physical design with VLSI CAD tools.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 355 [Min Grade: D] and (ECE 200 [Min Grade: D] or CS 270 [Min Grade: D])

ECEC 473 Modern VLSI IC Design 3.0 Credits

This is a project-oriented course where a high-complexity VLSI design project will be assigned to student teams. Team-work, task assignment and team communication will be mediated in an industry setting. Design tasks will cover the entire IC design flow range, from system specification to TRL description to timing and power analysis.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 472 [Min Grade: D]

ECEC 474 ASIC Design I 3.0 Credits

This course will focus exclusively on digital CMOS Application Specific Integrated Circuit (ASIC) systems design and automation. The ASIC physical design flow, including logic synthesis, floorplanning, placement, clock tree synthesis, routing and verification will be presented. These back-end physical design flow steps will also be covered through hands-on practice using industrial VLSI CAD tools. Contemporary design practices will be reviewed and presented in experiments.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECE 200 [Min Grade: D] and ECEC 355 [Min Grade: D]

ECEC 475 ASIC Design II 3.0 Credits

Design and analysis of Application Specific Integrated Circuits (ASICs) will be covered from a systems design perspective. System timing, arithmetic building block and memory block design processes will be presented. Design tasks in a quarter-long, small-complexity processor design project will cover the back-end of the IC design flow range, from RTL synthesis to timing and power analysis. Projects will be performed in a hierarchical group, similar to an industrial setting, with other graduate and undergraduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 474 [Min Grade: D]

ECEC 490 Special Topics in Computer Engineering 12.0 Credits

Provides special courses offered because of particular student or faculty interest.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

ECEC 497 Research In Computer Engineering 0.5-12.0 Credits

Computer engineering students only. Requires independent research in a field approved by the faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Can enroll if major is CE.

ECEC 499 Independent Study in Computer Engineering 0.5-12.0 Credits

Computer engineering students only. Requires independent study or research in a field approved by the faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Can enroll if major is CE.
Cannot enroll if classification is Freshman or Sophomore

Elec & Computer Engr-Electroph Courses

ECEE 302 Electronic Devices 4.0 Credits

Covers principles of operation of semiconductor devices, including PN diodes, bipolar transistors, and field effect transistors (JFET, MOSFET, MESFET). Applications of PN junctions, including solar cells, led, laser diodes. Laboratories reinforce lecture material by allowing students to build, measure and analyze data from simple devices.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: TDEC 211 [Min Grade: D] or ENGR 220 [Min Grade: D]

ECEE 304 Electromagnetic Fields & Waves 4.0 Credits

Covers vector calculus, Coulomb's Law, Gauss' Law, Ampere's Law, Maxwell's equations, Electromagnetic (EM) fields in devices, EM fields in circuits, EM fields in machinery, EM waves, biological effects.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: MATH 291 [Min Grade: D]

ECEE 352 Analog Electronics 4.0 Credits

Teaches the fundamentals of electronic circuit analysis and design by means of practical projects, such as a dc power supply and an audio amplifier. Covers design with discrete components as well as integrated circuit design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 302 [Min Grade: D] and ECES 301 [Min Grade: D]

ECEE 354 Wireless and Optical Electronics 4.0 Credits

Covers propagation of waves in various media as it relates to wireless communications: reflection, transmission, polarization, wave packets, dispersion, radiation and antennas, microwave electronic devices, optical wave guides, and fiber optics.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D] and ECEE 304 [Min Grade: D]

ECEE 390 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

ECEE 421 Advanced Electronics I 4.0 Credits

Application-and design-focused course. Analyzes feedback in electronic circuits such as operational amplifiers. Covers design and applications of active filters and other typical electronic circuitry. Includes experiments in the design of multistage transistor circuits, feedback loops, operational amplifiers, and active filters.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 352 [Min Grade: D]

ECEE 422 Advanced Electronic Circuits I 3.0 Credits

Application-and design-focused course. Covers analysis and design of communication circuits and non-linear active circuits; oscillators, mixers, IF and RF amplifiers; and AM and FM modulators.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 421 [Min Grade: D]

ECEE 423 Advanced Electronics Circuits II 3.0 Credits

Application-and design-focused course. Covers non-linear circuits; function and wave form generators; log-amp, multipliers, dividers, power amp, and phase-lock loops; and design of electronics needed to implement different logic circuit families.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 421 [Min Grade: D]

ECEE 434 Digital Electronics 4.0 Credits

Covers basic digital integrated circuit building blocks (inverters, nor and nand logic), CMOS logic gates (dc and transient behavior), drivers, and digital circuits and systems (PLA, gate array, memory). Experiments in semiconductor material characterization, device characterization, circuit and device simulations.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 302 [Min Grade: D]

ECEE 441 Lightwave Engineering I 3.0 Credits

Covers fundamentals of wave propagation, including propagation in various fiber wave guides and field distributions, diffraction, attenuation, dispersion, information capacity, and other analytic and design considerations in fiber systems. Fall.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 304 [Min Grade: D]

ECEE 442 Lightwave Engineering II 3.0 Credits

Covers operating principles, construction, and characteristics of sources, couplers, and detectors used in optical systems. Includes equivalent circuit models and principles of generation, transmission, and reception. Winter.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 441 [Min Grade: D]

ECEE 443 Lightwave Engineering III 3.0 Credits

Covers applications of devices and systems in such areas as data, voice, and image trans-mission; industrial automation; process control; medicine; and computers. Includes basic measurement systems. Spring.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 442 [Min Grade: D]

ECEE 451 Electroacoustics 3.0 Credits

Applications-oriented course. Covers fundamentals of vibrating systems; equations of motion; acoustical, electrical, and mechanical analogs; properties of waves in fluids; acoustic impedance and plane wave transmission; application to design of transducers; and application of acoustic waves in medical imaging, non-destructive testing, and the biomedical field.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman or Junior or Pre-Junior or Sophomore

ECEE 471 RF Components and Techniques 4.0 Credits

This course covers microwave networks (Z, Y, S, T ABCD Parameters), signal flowgraph, impedance matching techniques (lumped and distributed, quarter wave transformers), circulators and isolators, directional couplers (branch line, Wilkinson, Lange, slot waveguide), and filters (lowpass, bandpass, bandstop, highpass). CAD laboratory and design projects are an integral part of this course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 354 [Min Grade: D]

ECEE 472 RF Electronics 4.0 Credits

This course covers static and dynamic characteristics of transistors, unipolar (MOSFET, MESFET, HEMT), bipolar (BJT, HBT), LNA design and realization, power amplifiers, distributed amplifiers, switches, limiters, phase shifters, detectors, mixers, oscillators (Colpitts, YIG turned, reflection, transmission, DRO). CAD laboratory and design projects are an integral part of this course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 471 [Min Grade: D]

ECEE 473 Antennas and Radiating Systems 4.0 Credits

This course covers short and magnetic dipole, radiation pattern, radiation resistance, directivity and gain, line antennas (dipoles, monopoles, V and inverted V antennas), helix, Yagi-Uda, log-periodic, aperture antennas (slot, horn and reflector), printed circuit antennas (patch and spiral), and phased antennas. CAD laboratory and design projects are an integral part of this course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEE 471 [Min Grade: D]

ECEE 490 Special Topics in Electrophysics 12.0 Credits

Provides special courses offered because of particular student or faculty interest.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

ECEE 497 Research in Electrophysics 0.5-12.0 Credits

Requires independent research in a topic approved by the faculty.

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

ECEE 499 Independent Study In Electrophysics 0.5-12.0 Credits

Requires independent study in a topic approved by the faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

Elec & Computer Engr-Power Eng Courses

ECEP 352 Electric Motor Control Principles 4.0 Credits

Introduces machinery principles, magnetic circuits, three-phase circuits, the electrical and economic structure of the power industry, ac and dc machine fundamentals, and power electronic converters and their interfaces with electric motors. Some or all pre-requisites may be taken as either a pre-requisite or co-requisite. Please see the department for more information.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 302 [Min Grade: D] (Can be taken Concurrently)(ECE 201 [Min Grade: D] or ECES 211 [Min Grade: D])

ECEP 354 Energy Management Principles 4.0 Credits

Covers principles of power engineering, including the electrical and economic structure of the power industry (distribution, subtransmission, and bulk transmission levels; environmental issues; the electrical system analysis; the thermal system analysis; links between electromechanics and thermodynamics; and safety issues). Some or all pre-requisites may be taken as either a pre-requisite or co-requisite. Please see the department for more information.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 302 [Min Grade: D] (Can be taken Concurrently)(ECE 201 [Min Grade: D] or ECES 211 [Min Grade: D])

ECEP 371 Introduction to Nuclear Engineering 2.0 Credits

This course introduces the student to the fundamental topic of nuclear engineering. This course should be the first course for students interested in the nuclear engineering minor, as all of the topics will be discussed in greater detail in other courses. Topics include atomic and nuclear structure, binding energy, reaction kinetics and energetics, and radioactive decay.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: PHYS 201 [Min Grade: C] and (ENGR 210 [Min Grade: C] or CHE 206 [Min Grade: C])

ECEP 372 Radiation Detection and Measurement 3.0 Credits

Introduces students to the fundamentals of radiation detection, and applications of radiation detection equipment.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 371 [Min Grade: D] or ECEP 404 [Min Grade: D] or MEM 371 [Min Grade: D]

ECEP 380 Introduction to Renewable Energy 3.0 Credits

Introduction to Renewable Energy is an undergraduate survey course for engineers, scientists and others interested in energy systems and applications. The course introduces students to the mix of current major electric power sources and the pressures that are forcing a transition to renewable sources. Wind and solar energy will be studied in detail, with others as time allows. Course culminates with an integrating off-grid energy system design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: MATH 122 [Min Grade: D] and (PHYS 102 [Min Grade: D] or PHYS 115 [Min Grade: D] or PHYS 154 [Min Grade: D])

ECEP 390 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

ECEP 402 Theory of Nuclear Reactors 4.0 Credits

Introduces students to atomic and nuclear physics, radiation interaction with matter, components of nuclear reactors, neutron diffusion and moderation, nuclear reactor theory, and heat removal from nuclear reactors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ENGR 210 [Min Grade: D]

ECEP 403 Nuclear Power Plant Design & Operation 3.0 Credits

Introduces students to the design of nuclear power plants. Topics covered include electrical transmission, non-nuclear related equipment, fluid flow, heat transfer, thermodynamics, heat exchangers, pump, valves, piping and nuclear reactor design. Course includes a final project which is the design of a nuclear power plant.

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

ECEP 404 Introduction to Nuclear Engineering 2.0 Credits

Introduces the fundamental scientific, technical, social and ethical issues in nuclear engineering; nuclear reactions and readiation, radiation protection and control, nuclear energy production and utilization, nuclear fuel cycle, nuclear fuel cycle, nuclear materials, controlled fusion and thermonuclear plasma systems, basics of plasma physics and plasma chemistry, nuclear waste management, nuclear reactor safety, analysis of severe nuclear accidents, risk assessment and related issues of engineering ethics.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: PHYS 201 [Min Grade: D] and (ENGR 210 [Min Grade: D] or CHE 206 [Min Grade: D])

ECEP 406 Introduction to Radiation Health Principles 3.0 Credits

This course is intended to impart radiation safety knowledge to the nuclear engineering student. A fundamental knowledge of radiation safety is critical for all nuclear engineers.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: MEM 371 [Min Grade: D] or ECEP 404 [Min Grade: D]

ECEP 411 Power Systems I 3.0 Credits

Covers steady state generator, transformer and transmission line modeling used for balanced steady state power system analysis including three-phase to single-phase model conversion, per-unit analysis, generator and line loadability, transformer and transmission line voltage regulation and reactive compensation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 352 [Min Grade: D]

ECEP 412 Power Systems II 4.0 Credits

Covers y-bus based analysis of power systems including steady-state power-flow models and algorithms, economic dispatch of power generation, load-frequency control and introduction to transient stability analysis including time-domain simulation and equal area criterion.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 411 [Min Grade: D]

ECEP 413 Power Systems III 3.0 Credits

Covers Z-bus-based analysis of power systems including symmetrical component networks of generators, transformers, transmission lines and loads, symmetrical and unbalanced three-phase bus and line faults, and an introduction to power system protection.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 412 [Min Grade: D]

ECEP 421 Modeling and Analysis of Electric Power Distribution Systems 3.0 Credits

Introduction to power distribution systems; balanced and unbalanced systems, component and load modeling, radial and weekly meshed topologies; algorithms for unbalanced power studies including radial and general structure solver.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Corequisite: ECEP 411

ECEP 422 Power Distribution Automation and Control 3.0 Credits

Focuses on distribution management systems and their application: including optimizing network operation - capacitor placement and control, network reconfiguration, service restoration. Modern solution technologies are addressed.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 421 [Min Grade: C]

ECEP 423 Service and Power Quality Distribution Systems 3.0 Credits

Focus on 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
Prerequisites: ECEP 422 [Min Grade: C]

ECEP 431 Advanced Electromagnetic Energy Conversion I 4.0 Credits

Covers theory and operation of alternating current machinery, with emphasis on design alternatives and the effects of design on performance. Includes construction of machine models from laboratory measurements.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 352 [Min Grade: D]

ECEP 432 Advanced Electromagnetic Energy Conversion II 4.0 Credits

Covers dynamic behavior and transient phenomena of rotating machines and the mathematical models used to describe them, generalized machine theory, measurement of parameters for the mathematical models, and measurement of dynamic and transient behavior.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 431 [Min Grade: D]

ECEP 441 Protective Relaying 3.0 Credits

Covers operating principles of electromechanical and static relays, fault clearance, and protection of individual parts of a power system. Some or all pre-requisites may be taken as either a pre-requisite or co-requisite. Please see the department for more information.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 411 [Min Grade: D] (Can be taken Concurrently)ECEP 352 [Min Grade: D]

ECEP 451 Power Electronic Converter Fundamentals 3.0 Credits

Fundamentals of power electronics that include waveforms, basic power switch properties and magnetic circuits. Introduction to basic power electronic converter circuits: diode and phase-controlled rectifies and inverters; switch-mode converters. Applications to DC and AC power supply systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 352 [Min Grade: D]

ECEP 452 Experimental Study of Power Electronic Converters 3.0 Credits

Experimental study of common power electronic converters: diode rectifiers, phase-controlled rectifies, switch-mode inverters. Both hardware and software studies. Additional lectures on: Study of DC-DC switch-mode converters.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 451 [Min Grade: D]

ECEP 453 Applications of Power Electronic Converters 3.0 Credits

Provides a first look at various power electronic applications in residential, commercial and industrial sites. Examples include utility application such as static var compensators (SVC), thyristor switch capacitors (TSC), high voltage direct-current (HVDC) transmission systems among others. In addition, fundamentals of motor drives and their controls are covered. Examples include induction, DC synchronous and specialized motors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEP 451 [Min Grade: D]

ECEP 461 High Voltage Laboratory 1.0 Credit

Requires students to perform four basic experiments to become familiar with high-voltage techniques and then do a high-voltage design project of their own choosing.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEP 352 [Min Grade: D]

ECEP 471 Power Seminar I 0.5 Credits

Discusses current developments in power system operation and research, concentrating on current and future energy sources.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman

ECEP 472 Power Seminar II 0.5 Credits

Discusses current developments in power system operation and research, concentrating on generating stations, transmission lines, and substations.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman

ECEP 473 Power Seminar III 0.5 Credits

Discusses current developments in power system operation and research, concentrating on distribution, security, and economics.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman

ECEP 480 Solar Energy Engineering 3.0 Credits

Covers design of grid-connected and battery backup grid-connected photovoltaic systems. Both electrical and mechanical aspects are included. Topics include system components (solar cells, charge controllers, maximum power point trackers, inverters, etc.), system economics, computer and web-based design aids, electrical codes and standards, externalities of PV systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEE 302 [Min Grade: D] or ECEE 352 [Min Grade: D] or CHE 431 [Min Grade: D] or ECEP 380 [Min Grade: D]

ECEP 490 Special Topics in Power Engineering 12.0 Credits

Provides special courses offered because of particular student or faculty interest.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

ECEP 497 Research in Power Systems 0.5-12.0 Credits

Requires independent study in a topic approved by the faculty.

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

ECEP 499 Independent Study In Power Engineering 0.5-12.0 Credits

Requires independent study in a topic approved by the faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

Elec & Computer Engr-Systems Courses

ECES 201 Introduction to Audio-Visual Signals 4.0 Credits

This introductory engineering course will focus on the digital signal representations commonly used in prevailing entertainment media: audio, images, and video. It will explore how each medium is represented digitally and convey the signal processing concepts used in storing, manipulating, transmitting, and rendering such content. The goal of the course is to provide non-engineering students with a fundamental understanding of core digital signal processing methods.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: MATH 122 [Min Grade: D]

ECES 301 Transform Methods and Filtering 4.0 Credits

This course covers the engineering related concepts of signals and systems, their modeling and analysis. We discuss the problem of formulation of physical systems, plus mathematical solution of models (equations). Continuous-time signals and systems, discrete-time signals and systems, linear time-invariant systems, convolution integrals and sums, Fourier series, Fourier, Laplace and Z-transforms, and system functions will be studied.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (TDEC 221 [Min Grade: D] or ENGR 232 [Min Grade: D] or MATH 262 [Min Grade: D] or MATH 210 [Min Grade: D]) and ECE 201 [Min Grade: D]

ECES 302 Transform Methods and Filtering 4.0 Credits

Covers the Fourier series and the Fourier transform, sinusoidal steady-state analysis and filtering, discrete-time systems and the Z-transform, discrete Fourier transform, network functions and stability, magnitude, phase, poles and zeroes, Nyquist criterion, the Nyquist plot and root loci, stability of one-ports, sensitivity, worst-case design and failure-tolerance.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: (TDEC 221 [Min Grade: D] or ENGR 232 [Min Grade: D] or MATH 262 [Min Grade: D] or MATH 210 [Min Grade: D]) and ECE 201 [Min Grade: D]

ECES 303 Transform Methods II 3.0 Credits

This course covers the engineering related concepts of signals and systems, their modeling and analysis. We discuss the problem of formulation of physical systems, plus mathematical solution of models (equations). Continuous-time signals and systems, discrete-time signals and systems, linear time-invariant systems, convolution integrals and sums, Fourier series, Fourier, Laplace and Z-transforms, and system functions will be studied.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 301 [Min Grade: D]

ECES 304 Dynamic Systems and Stability 4.0 Credits

Covers linear time-invariant circuits and systems; two-and multi-terminal resistors, operational-amplifier circuits, first-order circuits, linear and nonlinear second-order systems, state equation and state variables, eigenvalues and eigenvectors, zero-input response, qualitative behavior of x'=Ax (stability and equilibria), qualitative behavior of x'=f(x), phase portraits, equilibrium states.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 301 [Min Grade: D]

ECES 306 Analog & Digital Communication 4.0 Credits

Covers signal sampling and reconstruction; modulation, angle modulation; digital communications systems, digital transmission.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D]

ECES 352 Introduction to Digital Signal Process 4.0 Credits

Covers discrete-time signals, analog-digital conversion, time and frequency domain analysis of discrete-time systems, analysis using Z-transform, introduction to digital filters, discrete-time Fourier transform, Discrete Fourier Transform (DFT), and Fast Fourier Transform (FFT).

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D]

ECES 354 Wireless, Mobile & Cellular Communications 4.0 Credits

Covers concepts of wireless systems; propagation effects, including loss, dispersion, fading, transmission, and reception; mobile systems, including design of base units and mobile units; micro cells and pico cells; cell division, including frequency use and reuse; concepts of FDMA, TDMA, and CDMA; error rates and outage probability; and circuits and components for wireless and mobile systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 306 [Min Grade: D]

ECES 356 Theory of Control 4.0 Credits

Covers the foundations of control theory. Includes experiments and demonstrations during lectures and labs that may be jointly held, taking advantage of multimedia and computer-controlled apparatus.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 304 [Min Grade: D]

ECES 358 Computer Control Systems 4.0 Credits

Reviews principles of applications of computer control systems to a variety of industries and technologies, including manufacturing processes, robotic cells, machine cells, chemical processes, network control, investment portfolio control, and real-time expert and learning systems for diagnostics and quality control.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 356 [Min Grade: D]

ECES 390 Special Topics 4.0 Credits

Provides special courses offered because of particular student or faculty interest.

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

ECES 411 Convex Optimization in Engineering Systems 3.0 Credits

Covers fundamental of convex optimization including convex sets, convex functions, linear and nonlinear constraints, complementary slackness, Lagrange multipliers, Lagrangian duality, and quadralic programming. Focuses on applications (e.g., signal processing, communications, computer networking, and portfolio management). Focuses on use of Matlab or equivalent software.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D] and (ENGR 361 [Min Grade: D] or ECE 361 [Min Grade: D])

ECES 412 Simulation of Stochastic Engineering Systems 3.0 Credits

Covers algorithms for generation of pseudo-random numbers, generation of random variates using the inverse transform, acceptance rejection techniques, Monte Carlo simulation, basics of point and interval estimation and hypothesis testing. Coverage of Markov chains, Markov chain Monte Carlo, Metropolis algorithm, simulated annealing, as time permits. Applications include computer networks, statistical physics, derivative pricing. Focus on use of Matlab or equivalent software.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D] and (ENGR 361 [Min Grade: D] or ECE 361 [Min Grade: D])

ECES 413 Strategies for Repeated Games 3.0 Credits

Covers the gambler’s ruin problem, optimality of bold play for subfair games, the Martingale betting system, Kelly betting and the maximum growth rate in superfair games, the multi-armed bandit and it generalizations, Parrondo’s paradox for coupled subfair games, basics of auction theory. Focus on use of Matlab or equivalent software.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D] and (ENGR 361 [Min Grade: D] or ECE 361 [Min Grade: D])

ECES 421 Communications I 3.0 Credits

Covers analog communications, including linear modulation methods (AM, DSB, SSB), exponential modulation (FM, PM), and noise effects on analog communication systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 306 [Min Grade: D]

ECES 422 Communications II 3.0 Credits

Covers analog (PAM, PPM) and digital (PCM, DM) pulse modulation systems, entropy, source coding, and channel coding.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 421 [Min Grade: D]

ECES 423 Communications III 3.0 Credits

Covers digital transmission systems, baseband and passband, spread-spectrum communications, and basics of wireless and mobile systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 422 [Min Grade: D]

ECES 434 Applied Digital Signal Processing 4.0 Credits

This course explores digital signal processing (DSP) concepts through the context of current applications, which range from video encoding to human genome analysis. Topics such as sampling, aliasing, and quantization, are considered in terms of the constraints of particular applications. Discrete-time linear systems, frequency-domain analysis, and digital filtering using Discrete Fourier Transform are examined in-depth and realized through application-specific lab projects.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 352 [Min Grade: D]

ECES 435 Recent Advances in Digital Signal Processing 4.0 Credits

Digital signal processing algorithms once thought to be impractical are now implemented in devices, such as household appliances & mobile phones. This course explores the computationally-intensive DSP methods including short-time linear prediction, cepstral analysis, and complex phase reconstruction as well as alternative signal representations and transforms, including the Hilbert, Chirp, and Discrete Cosine Transforms. Laboratory projects will focus on the implementation of these methods.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 352 [Min Grade: D]

ECES 436 Multi-disciplinary Digital Signal Processing 4.0 Credits

The applications of digital signal processing (DSP) span a wide range of problem domains and disciplines. This course explores the multi-disciplinary aspects of DSP by focusing on a core set of common methods applicable to problems in many fields, such as periodicity detection, signal and power spectrum estimation, and data modeling. Laboratory projects will utilize experiments drawn from a diversity of fields, including medicine, music analysis, image processing,voice/data communications and robotics.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 352 [Min Grade: D]

ECES 444 Systems and Control I 4.0 Credits

This course reviews classical control: analysis and design, state space approach to systems analysis and control; Eigenvalue/Eigenvector analysis, model decomposition, state space solutions and Cayley-Hamilton technique and applications.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 356 [Min Grade: D]

ECES 445 Systems and Control II 4.0 Credits

This course covers Eigenvector single-value decomposition and modal decomposition; controllability, observability and Kalman canonical forms; state controllers and observers and the separation principle.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 444 [Min Grade: D]

ECES 446 Systems and Control III 4.0 Credits

This course covers linear quadratic control, non-linear stability and analysis. Current topics in control include Robust, H-infinity, and Fuzzy Control concepts.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 445 [Min Grade: D]

ECES 462 Medical Robotics II 3.0 Credits

This course will review the emerging, multidisciplinary field of Medical Robotics. The course includes multiple site/field visits to observe Medical Robot systems demonstrations and interaction with the medical team and system manufacturers.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 461 [Min Grade: D]

ECES 490 Special Topics in Systems Engineering 12.0 Credits

Provides special courses offered because of particular student or faculty interest.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

ECES 497 Research in Systems Engineering 0.5-12.0 Credits

Electrical engineering students only. Requires independent research in a topic approved by the faculty.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit
Restrictions: Cannot enroll if classification is Freshman

ECES 499 Supervised Study in Systems Engineering 0.5-20.0 Credits

Requires independent study in a topic approved by the faculty.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman

Electrical & Computer Engr Courses

ECE 101 Electrical and Computer Engineering in the Real World 1.0 Credit

This seminar introduces students to highly visible and compelling applications of ECE through the use of familiar real-world applications. The course will highlight some of the high-impact advances of ECE and the importance of ECE in our daily lives. Fundamental concepts, such as electricity, light, computing, networking, and signal processing will be introduced in this context and explained at an introductory level. This course is intended to inspire students to pursue ECE and will lead them directly into ECE 102.

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

ECE 102 Applications of Electrical and Computer Engineering 2.0 Credits

Introduces the basic fundamentals of ECE through the use of real-world applications. The course will introduce Signals and Systems, Analog electronic basics, as well as Digital numbers and systems. The course will introduce students to basic ECE material, preparing the students for ECE 200 and ECE 201.

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

ECE 121 Introduction to Entertainment Engineering 3.0 Credits

This introductory survey course will focus on the four prevailing entertainment media: music, images, video, and games. We will explore how each medium is represented digitally and reveal the technologies used to capture, manipulate and display such content. Technical standards used in everyday entertainment devices (mp3, H.264, JPEG 1080p, HDMI) will be explained in layman's terms. The goal is to provide students with technical literacy for using digital media.

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

ECE 190 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

ECE 200 Digital Logic Design 3.0 Credits

Number systems and representation, two's complement arithmetic, digital logic devices, switching algebra, truth tables, minimization of Boolean functions, combinational logic design and analysis, sequential circuit analysis and design.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: CS 170 [Min Grade: D] or TDEC 132 [Min Grade: D] or CS 171 [Min Grade: D] or ENGR 103 [Min Grade: D] or ENGR 104 [Min Grade: D]

ECE 201 Foundations of Electric Circuits 3.0 Credits

Covers basic electric circuit concepts and laws; circuit theorems; mesh and node methods; analysis of first-and second-order electric circuits; force and natural response; sinusoidal steady state analysis; complex frequency.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if major is CAE or classification is Freshman
Prerequisites: PHYS 211 [Min Grade: D] or TDEC 115 [Min Grade: D] or PHYS 281 [Min Grade: D] or PHYS 102 [Min Grade: D]

ECE 203 Programming for Engineers 3.0 Credits

Fundamentals of computer organization; rudiments of programming including data types, arithmetic and logical expressions, conditional statements, control structures; problem solving techniques for engineers using programming; object-oriented programming; arrays; simulation of engineering systems; principles of good programming practice.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman

ECE 211 Electrical Engineering Principles 3.0 Credits

Not open to electrical or mechanical engineering students. Covers basic techniques of electric circuit analysis, electronic devices, amplifiers, operational amplifier, and fundamentals of instrumentation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if major is EE or major is MECH or classification is Freshman
Prerequisites: (MATH 201 [Min Grade: D] or ENGR 231 [Min Grade: D] or MATH 261 [Min Grade: D]) and (PHYS 211 [Min Grade: D] or PHYS 281 [Min Grade: D] or PHYS 102 [Min Grade: D])
Corequisite: ECE 212

ECE 212 Electrical Engineering Principles Laboratory 1.0 Credit

Not open to electrical or mechanical engineering students. Includes experiments involving concepts discussed in ECE 211.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if major is EE or major is MECH or classification is Freshman
Corequisite: ECE 211

ECE 290 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

ECE 361 Probability for Engineers 3.0 Credits

This course will cover topics related to probability and statistics. Probability topics include sample space and probability, discrete and continuous random variables, expectation, variance, covariance, correlation, conditional expectation, conditional variance, the weak and strong law of large numbers and the central limit theorem. Statistics topics include properties of a random sample, principles of data reduction, and point estimation.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ENGR 202 [Min Grade: D] and (ENGR 231 [Min Grade: D] or MATH 261 [Min Grade: D])

ECE 362 Engineering Statistics 3.0 Credits

This course will cover topics related to statistics and probability. Probability topics include sample space and probability; discrete and continuous random variables, expectation, variance, the law of large numbers and the central limit theorem. Statistics topics include properties of a random sample, principles of data reduction, point estimation, hypothesis testing, interval estimation, and linear regression.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ENGR 202 [Min Grade: D] and ENGR 231 [Min Grade: D]) or (ENGR 202 [Min Grade: D] and MATH 261 [Min Grade: D])

ECE 390 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

ECE 391 Introduction to Engineering Design Methods 1.0 Credit

Introduces the design process, including information retrieval, problem definition, proposal writing, patents, and design notebooks. Includes presentations on problem areas by experts from industry, government, and education.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Junior or Senior.

ECE 491 [WI] Senior Design Project I 2.0 Credits

Introduces the design process, including information retrieval, problem definition, proposal writing, patents, and design notebooks. Includes presentations on problem areas by experts from industry, government, and education. This is a writing intensive course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.

ECE 492 [WI] Senior Design Project II 2.0 Credits

Continues ECE 491. Requires written and oral progress reports. This is a writing intensive course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECE 491 [Min Grade: D]

ECE 493 Senior Design Project III 4.0 Credits

Continues ECE 492. Requires written and oral final reports, including oral presentations by each design team at a formal Design Conference open to the public and conducted in the style of a professional conference.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is Senior.
Prerequisites: ECE 492 [Min Grade: D]

Electrical Engineering Lab Courses

ECEL 301 [WI] Electrical Engineering Laboratory 2.0 Credits

Offers laboratory experiences in each of the five ECE tracks: computers, controls/robotics, electronics, power and energy, and telecommunications. Each lab consists of a stand-alone module containing: lecture material providing basic theory, references, and laboratory experiments. This is a writing intensive course.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECE 200 [Min Grade: D] and ECE 201 [Min Grade: D] and (TDEC 132 [Min Grade: D] or TDEC 133 [Min Grade: D] or ENGR 104 [Min Grade: D] or ENGR 103 [Min Grade: D])

ECEL 302 ECE Laboratory II 2.0 Credits

Offers laboratory experiences in each of the five ECE tracks: computers, controls/robotics, electronics, power and energy, and telecommunications. Each lab consists of a stand-alone module containing: lecture material providing basic theory, references, and laboratory experiments. Some or all pre-requisites may be taken as either a pre-requisite or co-requisite. Please see the department for more information.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECES 301 [Min Grade: D] (Can be taken Concurrently)ECEL 301 [Min Grade: D]

ECEL 303 ECE Laboratory III 2.0 Credits

Covers basic digital signal processing concepts, an introduction to analog-to-digital and digital-to-analog converters, and power supply design using analog IC devices.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: ECEL 302 [Min Grade: D]

ECEL 304 ECE Laboratory IV 2.0 Credits

This course offers laboratory experience, using both modeling software and digital and analog hardware relevant to both electrical and computer engineers. Multi-week design projects and design teams are used to prepare students for Senior Design work.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEL 303 [Min Grade: D]

ECEL 311 ECE Laboratory Methods I 3.0 Credits

Introduces students to MATLAB and PSpice, industry standard CAD software for electronics (analog and digital) and systems engineers. Solve DC bias, DC sweep, AC sweep, and transient problems in PSpice and MATLAB. Build and design simple digital circuits.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECE 200 [Min Grade: D] and ECE 201 [Min Grade: D] and ENGR 103 [Min Grade: D]

ECEL 312 ECE Laboratory Methods II 3.0 Credits

Covers introduction to transistor circuits, PSpice simulations of active devices, transfer function analysis, Bode analysis, active filter analysis and design. Programming and use of Microprocessors and/or FPGA. Perform measurements on devices and circuits.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECEL 301 [Min Grade: D] or ECEL 311 [Min Grade: D]

ECEL 401 Lightwave Engineering Laboratory 3.0 Credits

Teaches fundamentals of interaction of light with matter. Waves and photons. nterference and diffraction. Optical fibers and free-space optics. Introduces students to optical communication and imaging.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D] and ECEE 302 [Min Grade: D]) or (ECEL 311 [Min Grade: D] and ECEL 312 [Min Grade: D] and ECEE 304 [Min Grade: D])

ECEL 402 Nano-Photonics Laboratory 3.0 Credits

Teaches a fundamental knowledge of nanophotonic materials, devices, and applications in a hands-on laboratory setting. Introduces students to photonic bandgaps, photonic crystals, optical sensing methods, holography methods and materials, concepts of surface plasmons and Plasmon resonance.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D] and ECEE 304 [Min Grade: D]) or (ECEL 311 [Min Grade: D] and ECEL 312 [Min Grade: D] and ECEE 304 [Min Grade: D])

ECEL 403 Bio-Photonics Laboratory 3.0 Credits

Teaches the fundamentals of the interaction of light with matter. Introduces students to different types of optical detection for biomedical applications,Quantized states of matter, Energy levels of atoms and molecules, Absorption, Scattering, Fluorescence, Imaging of cells and molecules, Spectroscopy, and Cancer precursors.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D] and ECEE 304 [Min Grade: D]) or (ECEL 311 [Min Grade: D] or ECEL 312 [Min Grade: D] or ECEE 304 [Min Grade: D])

ECEL 404 Software Defined Radio Laboratory 3.0 Credits

This course introduces students to the concept of software defined radio using the USRP hardware platform and GNU Radio software. Functional blocks of wireless communications systems will be discussed, programmed in Python, and tested on hardware.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D] and ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D]) or (ECEL 311 [Min Grade: D] and ECEL 312 [Min Grade: D] and ECES 301 [Min Grade: D] and ECES 303 [Min Grade: D])

ECEL 405 Digital Systems Laboratory 3.0 Credits

Students will gain practical knowledge of digital systems and signal processing by designing, simulating, constructing, testing and refining a digital audio recording system.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D] and ECES 301 [Min Grade: D]) or (ECEL 311 [Min Grade: D] and ECEL 312 [Min Grade: D] and ECES 301 [Min Grade: D])

ECEL 407 General Purpose GPU Programming 3.0 Credits

This course will teach students how to develop parallel algorithms for the GPU and implement them using the CUDA progamming interface.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: (ECEL 301 [Min Grade: D] and ECEL 302 [Min Grade: D] and ECEC 301 [Min Grade: D] and ECEC 355 [Min Grade: D]) or (ECEL 311 [Min Grade: D] and ECEL 312 [Min Grade: D] and ECEC 301 [Min Grade: D] and ECEC 355 [Min Grade: D])

ECEL 490 Special Topics 1.0-4.0 Credit

Provides special courses offered because of particular student or faculty interest.

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

Electrical and Computer Engineering Faculty

Pramod Abichandani, PhD (Drexel University). Assistant Teaching Professor. Optimal, multi-dimensional, data-driven decision-making, through the use of techniques from mathematical programming, linear and nonlinear systems theory, statistics, and machine learning.
Suryadevara Basavaiah, PhD (University of Pennsylvania). Teaching Professor. Computer engineering; computer engineering education; custom circuit design; VLSI technology; process and silicon fabrication.
Tom Chmielewski, PhD (Drexel University). Assistant Teaching Professor. Modeling and simulation of electro-mechanical systems; Optimal, Adaptive and Non-Linear Control; DC Motor Control; System Identification; Kalman Filters (Smoothing Algorithms, tracking); image processing, Robot design; Biometric technology and design of embedded systems for control applications utilizing MATLAB and SIMULINK
Fernand Cohen, PhD (Brown University). Professor. Surface modeling; tissue characterization and modeling; face modeling; recognition and tracking.
Andrew Cohen, PhD (Rensselaer Polytechnic Institute). Associate Professor. Image processing; multi-target tracking; statistical pattern recognition and machine learning; algorithmic information theory; 5-D visualization.
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, PhD (Drexel University). Professor. Microwave photonics systems; nonlinear microwave circuits; RFIC and wireless communications; antennas and radiating systems; electromagnetic interaction with biological systems.
Bruce A. Eisenstein, PhD (University of Pennsylvania) Arthur J. Rowland Professor of Electrical and Computer Engineering; Vice Dean, College of Engineering. Professor. Pattern recognition; estimation; decision theory; digital signal processing.
Adam K. Fontecchio, PhD (Brown University) Associate Dean for Undergraduate Affairs; Associate Director, Expressive and Creative Interactive Technologies (EXCITE) Center. 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 EDE Department Head; Liason 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). 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, PE (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. Neural networks; the study of aesthetics; artificial intelligence; music perception.
Youngmoo Kim, PhD (Massachusetts Institutie of Technology) Director, Expressive and Creative Interaction Technologies (EXCITE) Center. Associate Professor. Audio and music signal processing, voice analysis and synthesis, music information retrieval, machine learning.
Timothy P. Kurzweg, PhD (University of Pittsburgh) Associate Department Head for Undergraduate Studies and Director of the BSE Program. Associate Professor. Optical MEM modeling and simulation; system-level simulation; computer architecture.
Mohammad Madihian, PhD (Shizuoka University). Adjunct Professor. Solid-state device-circuit interaction; microwave and millimeter-wave monolithic circuit design and evaluation technology; solid-state power generation/amplification/mixing technology; single/multi-mode wireless RF/IF transceiver technology
Karen Miu, PhD (Cornell University). Professor. Power systems; distribution networks; distribution automation; optimization; system analysis.
Bahram Nabet, PhD (University of Washington). 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.
Vasileios Nasis, PhD (Drexel University). Associate Teaching Professor. Imaging with MOEMS, Projection systems using MEMS/MOEMS, Wireless communications, Remote monitoring, sensor networks.
Dagmar Niebur, PhD (Swiss Federal Institute of Technology). Associate Professor. Intelligent systems; dynamical systems; power system monitoring and control.
Chika Nwankpa, PhD (Illinois Institute of Technology) Interum Department Head. Professor. Power system dynamics; power electronic switching systems; optically controlled high power switches.
Christopher Peters, PhD (University of Michigan, Ann Arbor). Teaching Professor. Nuclear reactor design; ionizing radiation detection; nuclear forensics; power plant reliability and risk analysis; naval/marine power and propulsion; directed energy/high power microwaves; nonstationary signal processing; radar; electronic survivability/susceptibility to harsh environments; electronic warfare.
Karkal S. Prahbu, PhD (Harvard University). Teaching Professor. Computer and software engineering; advanced microprocessors and distributed operating systems.
Richard Primerano, PhD (Drexel University). Assistant Teaching Professor. Biologically inspired robotics, robot locomotion, signal processing, ultrasonic data transmission.
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.
Ioannis Savidis, PhD (University of Rochester) Director of the Integrated Circuits and Electronics (ICE) Design and Analysis Laboratory. Assistant Professor. Analysis, modeling, and design methodologies for high performance digital and mixed-signal integrated circuits; Emerging integrated circuit technologies; Electrical and thermal modeling and characterization, signal and power integrity, and power and clock delivery for 3-D IC technologies.
Kevin J. Scoles, PhD (Dartmouth College). 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.
James Shackleford, PhD (Drexel University). Assistant Professor. Medical image processing, high performance computing, embedded systems, computer vision, machine learning.
P. Mohana Shankar, PhD (Indian Institute of Technology) Allen Rothwarf Professor of Electrical and Computer Engineering. Professor. Wireless communications; biomedical ultrasonics; fiberoptic bio-sensors.
Matthew Stamm, PhD (University of Maryland, College Park) Head, Multimedia and Information Security Laboratory (MSL). Assistant Professor. Information Security; Multimedia Forensics and Anti-Forensics; Information Verification; Adversarial Dynamics; Signal Processing.
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.
Yon Visell, PhD (McGill University). Assistant Professor. Haptic display engineering, material and biomechanical contact physics, neuroscientific and physical basis of human tactile sensation/perception, haptic human-machine interaction, sensorimotor learning, interaction in virtual reality
John Walsh, PhD (Cornell University). Associate 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) Sr. Associate Dean for Computing and CCI Academic Affairs. 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 Dean, Strategic Planning, College of Engineering. 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

Robert Fischl, PhD (University of Michigan) John Jarem Professor Emeritus / Founder of the 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.
Oleh Tretiak, ScD (MIT). Professor Emeritus. Image processing; tomography; image registration; pattern recognition.
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