Computer Engineering

Major: Computer Engineering
Degree Awarded: Bachelor of Science in Computer Engineering (BSCE)
Calendar Type: Quarter
Total Credit Hours: 183.0
Co-op Options: Three Co-op (Five years); One Co-op (Four years)
Classification of Instructional Programs (CIP) code: 14.0901
Standard Occupational Classification (SOC) code: 15-1132; 15-1133; 15-1143; 17-2031

About the Program

The major provides a broad focus on electronic circuits and systems, computer architecture, computer networking, embedded systems, programming and system software, algorithms, and computer security. 

Computer engineers design smaller, faster, and more reliable computers and digital systems, build computer networks to transfer data, embed microprocessors in larger physical systems such as cars and planes, work on theoretical issues in computing, and design large-scale software systems. 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, www.abet.org.

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

For advising questions, please contact the ECE advisor.

Degree Requirements

Students must take ENGL 101

General Education/Liberal Studies Requirements
CIVC 101Introduction to Civic Engagement1.0
ENGL 101Composition and Rhetoric I: Inquiry and Exploratory Research3.0
ENGL 102Composition and Rhetoric II: Advanced Research and Evidence-Based Writing3.0
ENGL 103Composition and Rhetoric III: Themes and Genres3.0
PHIL 315Engineering Ethics3.0
UNIV E101The Drexel Experience1.0
COM Elective *3.0
General Education Requirements **15.0
Foundation Requirements
CHEM 101General Chemistry I3.5
ECE 105Programming for Engineers II3.0
ECE 200Digital Logic Design4.0
ECE 201Foundations of Electric Circuits I4.0
ENGR 111Introduction to Engineering Design & Data Analysis3.0
ENGR 113First-Year Engineering Design3.0
ENGR 131Introductory Programming for Engineers3.0
or ENGR 132 Programming for Engineers
ENGR 231Linear Engineering Systems3.0
ENGR 232Dynamic Engineering Systems3.0
MATH 121Calculus I4.0
MATH 122Calculus II4.0
MATH 200Multivariate Calculus4.0
MATH 281Linear Algebra with ECE Applications3.0
PHYS 101Fundamentals of Physics I4.0
PHYS 102Fundamentals of Physics II4.0
PHYS 201Fundamentals of Physics III4.0
Science Elective ***4.5
Professional Requirements
CS 260Data Structures3.0
CS 265Advanced Programming Tools and Techniques3.0
ECE 301Foundations of Electric Circuits II4.0
ECE 303ECE Laboratory3.0
ECE 361Probability for Engineers4.0
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 201Advanced Programming for Engineers3.0
ECEC 204Design with Microcontrollers3.0
ECEC 302Digital Systems Projects3.0
ECEC 355Computer Organization & Architecture3.0
ECEC 357Introduction to Computer Networks3.0
ECES 301Signals and Systems I4.0
MATH 221Discrete Mathematics3.0
Computer Engineering Electives 27.0
Free Electives15.0
Total Credits183.0

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 Program. 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.

Sample Plan of Study

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 111Introduction to Engineering Design & Data Analysis3.0
MATH 121Calculus I4.0
UNIV E101The Drexel Experience1.0
 Term Credits14.5
Term 2
CIVC 101Introduction to Civic Engagement1.0
ENGR 131
or 132
Introductory Programming for Engineers
Programming for Engineers
3.0
MATH 122Calculus II4.0
PHYS 101Fundamentals of Physics I4.0
General Education Elective*3.0
 Term Credits15.0
Term 3
ECE 105Programming for Engineers II3.0
ENGL 102Composition and Rhetoric II: Advanced Research and Evidence-Based Writing3.0
ENGR 113First-Year Engineering Design3.0
MATH 200Multivariate Calculus4.0
PHYS 102Fundamentals of Physics II4.0
 Term Credits17.0
Term 4
ECE 200Digital Logic Design4.0
ECEC 201Advanced Programming for Engineers3.0
ENGR 231Linear Engineering Systems3.0
PHYS 201Fundamentals of Physics III4.0
COM Elective**3.0
 Term Credits17.0
Term 5
ECE 201Foundations of Electric Circuits I4.0
ECEC 204Design with Microcontrollers3.0
ENGL 103Composition and Rhetoric III: Themes and Genres3.0
ENGR 232Dynamic Engineering Systems3.0
MATH 281Linear Algebra with ECE Applications3.0
 Term Credits16.0
Term 6
ECE 301Foundations of Electric Circuits II4.0
ECE 361Probability for Engineers4.0
ECEC 302Digital Systems Projects3.0
ECEC 357Introduction to Computer Networks3.0
 Term Credits14.0
Term 7
ECEC 355Computer Organization & Architecture3.0
ECES 301Signals and Systems I4.0
MATH 221Discrete Mathematics3.0
PHIL 315Engineering Ethics3.0
Free Elective3.0
 Term Credits16.0
Term 8
CS 265Advanced Programming Tools and Techniques3.0
ECE 303ECE Laboratory3.0
Two ECE Electives***6.0
General Education Elective*3.0
 Term Credits15.0
Term 9
CS 260Data Structures3.0
ECE 391Introduction to Engineering Design Methods (Also offered spring term.)1.0
One ECE Elective***3.0
Science Elective4.5
General Education elective*3.0
 Term Credits14.5
Term 10
ECE 491 [WI] Senior Design Project I2.0
One ECEC 4XX Elective††3.0
One ECE Elective***3.0
General Education Elective*3.0
Free Elective 3.0
 Term Credits14.0
Term 11
ECE 492 [WI] Senior Design Project II2.0
One ECEC 4XX Elective††3.0
One ECE Elective***3.0
General Education Elective*3.0
Free Elective 3.0
 Term Credits14.0
Term 12
ECE 493Senior Design Project III4.0
One ECEC 4XX Elective††3.0
One ECE Elective***3.0
Two Free Electives6.0
 Term Credits16.0
Total Credit: 183.0

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:

  • Lockheed Martin
  • Comcast Corporation
  • SAP America
  • Susquehanna International Group LLC
  • PJM Interconnection, LLC
  • Dell
  • National Board of Medical Examiners
  • UNISYS Corporation
  • Woodward McCoach, Inc.
  • NAVSEA
  • ClarivateAnalytics (Thomson Reuters)
  • NVIDIA
  • Excelon Corporation

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

Dual Degree Bachelor's Program

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.

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.

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.

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.

Computer Engineering Faculty

Juadelice Cavalcante de Oliveira, PhD (Georgia Institute of Technology). Associate Professor. Software-defined networking; social and economic networks; network security; design and analysis of protocols, algorithms and architectures in computer networks, particularly solutions for the Internet of Things
Tom Chmielewski, PhD (Drexel University). 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, ScD (Drexel University). Professor. Digital and microwave photonics; nonlinear microwave circuits; RFIC; medical imaging.
Anup Das, PhD (National University of Singapore). Assistant Professor. Design of algorithms and architecture for neuromorphic computing; machine learning particularly unsupervised learning using spiking neural networks; in-memory computing using non-volatile memories
Bruce A. Eisenstein, PhD (University of Pennsylvania) Vice Dean, College of Engineering; Arthur J. Rowland Professor. Professor. Pattern recognition; estimation; decision theory.
Adam K. Fontecchio, PhD (Brown University) Director, Center for the Advancement of STEM Teaching and Learning Excellence (CASTLE). Professor. Electro-optics; remote sensing; active optical elements; liquid crystal devices.
Gary Friedman, PhD (University of Maryland-College Park) Associate Department Head for Graduate Affairs. Professor. Biological and biomedical applications of nanoscale magnetic systems.
Allon Guez, PhD (University of Florida). Professor. Intelligent control systems; robotics, biomedical, automation and manufacturing; business systems engineering.
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.
Nagarajan Kandasamy, PhD (University of Michigan) Associate Department Head for Undergraduate Affairs. Professor. Embedded systems, self-managing systems, reliable and fault-tolerant computing, distributed systems, computer architecture, and testing and verification of digital systems.
Youngmoo Kim, PhD (MIT). Professor. Audio and music signal processing, voice analysis and synthesis, music information retrieval, machine learning.
Fei Lu, PhD (University of Michigan-Ann Arbor). Assistant Professor. Power electronics.
Karen Miu, PhD (Cornell University). Professor. Power systems; distribution networks; distribution automation; optimization; system analysis.
Bahram Nabet, PhD (University of Washington) Associate Dean for Special Projects, College of Engineering; Electrical and Computer Engineering. Professor. Optoelectronics; fabrication and modeling; fiber optic devices; nanoelectronics; nanowires.
Prawat Nagvajara, Ph.D. (Boston University). Associate Professor. System on a chip; embedded systems; power grid computation; testing of computer hardware; fault-tolerant computing; VLSI systems; error control coding.
Dagmar Niebur, PhD (Swiss Federal Institute of Technology). Associate Professor. Intelligent systems; dynamical systems; power system monitoring and control.
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
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.
Ionnis Savidis, PhD (University of Rochester). 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). Assistant Professor. Information Security; multimedia forensics and anti-forensics; information verification; adversarial dynamics; signal processing
Baris Taskin, PhD (University of Pittsburgh). Professor. Electronic Design Automation (EDA) of VLSI Circuits; high-performance circuits; resonant clocking; integrated circuit (IC) physical design; nanoarchitectures; and wireless IC interconnects
John Walsh, PhD (Cornell University). Associate Professor. Bounding the region of entropic vectors and its implications for the limits of communication networks, big data distributed storage systems, and graphical model based machine learning; efficient computation and analysis of rate regions for network coding and distributed storage: code construction, polyhedral computation, enumeration, hierarchy, and symmetry
Steven Weber, PhD (University of Texas-Austin) Interim Department Head. 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. Software-defined networking; social and economic networks; network security; design and analysis of protocols, algorithms and architectures in computer networks, particularly solutions for the Internet of Things
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