Electrical and Computer Engineering

Faculty and Research Interests

D. R. Brown, Professor and Department Head; Ph.D., Cornell University. Signal processing, synchronization, control systems, inference, and wireless networks.
M. M. Asheghan, Assistant Teaching Professor, PhD. University of Carlos III, Madrid, Spain. Robust control, statistical shape analysis, complex networks' synchronization, chaotic systems, convex optimization, soft robotics, machine mearning. 
S. V. Bhada, Assistant Professor, Ph.D., University of Alabama at Huntsville. Modeling and Analysis of Policy Content and Systems Engineering.
E. A. Clancy, Professor; Ph.D., MIT. Biomedical signal processing and modeling, biomedical instrumentation.
Y. Doroz, Assistant Teaching Professor; Ph.D., Worcester Polytechnic Institute. Blockchains and cryptocurrencies,  post-quantum cryptography, fully homomorphic encryption schemes and applications, accelerating Cryptographic applications using hardware/software co-designs.
F. Ganji, Assistant Professor; Ph.D. Technical University of Berlin (Germany). Security, machine learning, cryptography, privacy-preserving AI. 
U. Guler, Associate Professor, Ph.D., Bogozici University, Turkey. Smart Health Applications, Implantables and Wearables, Sensor Interfaces, Neural Interfaces, RF-Energy Harvesting, Wireless Power and Data Transfer, Power Management IC, Biomedical Security, and, Low Power Analog/Mixed Signal IC Design.
X. Huang, Professor; Ph.D., Virginia Tech. Autonomous vehicles; computer vision; machine learning; FPGA and VLSI design; internet of things.
B. Islam, Assistant Professor, Ph.D., University of North Carolina at Chapel Hill. Machine Learning, especially Efficient and On-Device Deep Learning, Mobile and Ubiquitous Computing, Cyber-Physical Systems, Internet of Things, and Mobile Health
R. Ludwig, Professor and Associate Department Head; Ph.D., Colorado State University. Design of RF coils for magnetic resonance imaging; amplifier design; nondestructive material evaluation.
S. N. Makaroff, Professor; Ph.D., Dr. Sci, St. Petersburg State University (Russian Federation). Bioelectromagnetics, Electromagnetic therapeutic devices, Antennas and electromagnetic sensors. Human body CAD models.
J. A. McNeill, Professor and Dean of Engineering; Ph.D., Boston University. Analog IC design; high-speed imaging; mixed-signal circuit characterization.
K. Mus, Assistant Teaching Professor; Ph.D., Middle East Technical University, Turkey. Cybersecurity, post-quantum cryptography, fault attacks.
P. Schaumont, Professor; Ph.D., University of California at Los Angeles. Hardware security; reverse engineering; embedded systems; hardware-software codesign; digital IC design.
B. Sunar, Professor; Ph.D., Oregon State University . Cybersecurity; applied cryptography; high-speed computing.
S. Tajik, Assistant Professor; Ph.D., Technical University of Berlin, Germany. Non-invasive and semi-invasive side-channel analysis, Physically Unclonable Functions (PUFs), machine learning, FPGA security, and designing anti-tamper mechanisms against physical attacks
B. Tang, Associate Professor, Ph.D., University of Rhode Island. Machine learning, signal and information processing, control systems, cyber-physical systems. 
E. Uzunovic, Assistant Teaching Professor; Ph.D., University of Waterloo, Canada.  High voltage, direct current power transmission, advanced power distribution, power electronics including smart inverters.
A. M. Wyglinski, Professor and Associate Dean of Graduate Studies; Ph.D., McGill University . Cognitive radio, 4G/5G/6G/Next-G, spectrum sensing and co-existence, machine learning-based data transmission techniques, GPS and satellite communications, connected and autonomous vehicles, software-defined radio prototyping and test-beds, millimeter wave transmission, rural broadband and the Digital Divide.
Z. Zhang, Assistant Professor; Ph.D., Oxford Brookes University, UK. Computer vision and machine learning, especially in object recognition/detection, data-efficient learning.

Emeritus

K. A. Clements, D. Cyganski, J. S. Demetry, F. J. Looft, J. A. Orr, P. C. Pedersen

Affiliated Faculty

E. Agu (CS), G. Fischer (ME), C Furlong (ME), W. R. Michalson (RBE), L. Ramdas Ram-Mohan (PH), J. Sullivan (ME)

Programs of Study

The Electrical and Computer Engineering (ECE) Department offers programs leading to M.Eng., M.S. and Ph.D. degrees in electrical and computer engineering, an M.Eng. degree in power systems engineering (PSE), as well as graduate and advanced certificates. The following general areas of specialization are available to help students structure their graduate courses: Cybersecurity and Privacy, Microelectronics, Power Systems Engineering, Signals, Systems, and Communications.

The M.S. ECE degree is designed to provide an individual with advanced knowledge in one or more electrical and computer engineering areas via successful completion of at least 21 credits of WPI ECE graduate courses (including M.S. thesis credit), combined with up to 9 credits of coursework from computer science, mathematics, physics and other engineering disciplines.

The M.Eng. ECE and M.Eng. PSE degrees are tailored for individuals seeking an industrial career path. Similar to the M.S. degree, the M.Eng. degree requires the successful completion of at least 21 credits of WPI ECE graduate courses (specific course requirements for the M.S. ECE and M.S. PSE degrees are discussed below). In contrast to the M.S. degree, the M.Eng. degree allows up to 9 credits on non-ECE courses to be chosen as management courses and does not include a thesis option.

Admission Requirements

Master’s Program

Students with a B.S. degree in electrical engineering or electrical and computer engineering may submit an application for admission to the Master’s program. There are three degree options in the Master’s program: An M.S. in Electrical and Computer Engineering, an M.Eng. in Electrical and Computer Engineering, and an M.Eng. in Power Systems Engineering. Admission to the Master’s program will be based on a review of the application and associated references.

Applicants without a B.S. degree in electrical engineering or electrical and computer engineering, but who hold a B.S. degree in mathematics, computer engineering, physics or another engineering discipline, may also apply for admission to the Master’s program in the Electrical and Computer Engineering Department. If admitted, the applicant will be provided with required courses necessary to reach a background equivalent to the B.S. degree in electrical engineering or electrical and computer engineering, which will depend on the applicant’s specific background.

Applicants with the bachelor of technology or the bachelor of engineering technology degree must typically complete about 1-1/2 years of undergraduate study in electrical engineering before they can be admitted to the graduate program. If admitted, the applicant will be provided with required courses necessary to reach a background equivalent to the B.S. degree in electrical engineering or electrical and computer engineering, which will depend on the applicant’s specific background.

Ph.D. Program

Students with a Master’s degree in electrical and computer engineering may apply for the doctoral program of study. Admission to the Ph.D. program will be based on a review of the application and associated references. Students with a Bachelor of Science degree in electrical and computer engineering may also apply to the Ph.D. program. Students with a strong background in areas other than Electrical and Computer Engineering will also be considered for admission into the Ph.D. program. If admitted (based on review of the application and associated references), the applicant may be approved for direct admission to the Ph.D. program, or to an M.S.-Ph.D. program sequence. Applicants possessing and M.S. degree in electrical and computer engineering from WPI that have not been directly admitted to the Ph.D. program are still required to submit an application and associated references for consideration, with the exception of GRE scores, TOEFL scores, and the application fee.

Certificate Requirements

The ECE Department offers advanced certificate and graduate certificate programs. Please visit https://www.wpi.edu/academics/study/electrical-computer-engineering-certificates

Degree Requirements

There are three degree options within the Master’s program in the Electrical and Computer Engineering Department: A Master of Engineering in Electrical and Computer Engineering (M.Eng. ECE), a Master of Science in Electrical and Computer Engineering (M.S. ECE), and a Master of Engineering in Power Systems Engineering (M.Eng. PSE).

Program of Study

Each student must submit a program of study for approval by the student’s advisor, the ECE Department Graduate Program Committee and the ECE Department Head. To ensure that the Program of Study is acceptable, students should, in consultation with their advisor, submit it to the ECE Department Graduate Secretary prior to the end of the semester following admission into the graduate program. Students must obtain prior approval from the ECE Department Graduate Program Committee for the substitution of courses in other disciplines as part of their academic program.

All full-time students in the Master’s degree program (with the exception of B.S./M.S. students as noted below) are required to attend and pass the two graduate seminar courses, ECE 596A (fall semester) and ECE 596B (spring semester). See course listings for details.

Thesis Option

Students pursuing an M.S. ECE degree that are financially supported by the department in the form of teaching assistantship, research assistantship, or fellowship are required to complete a thesis. The thesis option is not available for students pursuing an M.Eng. ECE or M.Eng. PSE degree. M.S. thesis research involves 9 credit hours of work, registered under the designation ECE 599, normally spread over at least one academic year. For students completing the M.S. thesis as part of their degree requirements, a thesis committee will be set up during the first semester of thesis work. This committee will be selected by the student in consultation with the major advisor and will consist of the thesis advisor (who must be a full-time WPI ECE faculty member) and at least two other faculty members whose expertise will aid the student’s research program. An oral presentation before the Thesis Committee and a general audience is required. In addition, all WPI thesis regulations must be followed.

Non-Thesis Option

Although the thesis is optional for M.S. ECE students not financially supported by the department, and there is no thesis option available for M.Eng. ECE or M.Eng. PSE students, all M.Eng. and M.S. students are encouraged (but not required) to include a research component in their graduate program. A directed research project, registered under the designation ECE 598, provides an opportunity to conduct focused research under the direct supervision of an ECE faculty member. Credits received under the directed research designation (ECE 598) can be used to satisfy the M.Eng. ECE, M.Eng. PSE, and M.S. ECE degree requirements with a grade of C or better. Note that credit received under the thesis designation (ECE 599) may not be applied toward an M.Eng. ECE degree, M.Eng. PSE degree, or non-thesis M.S. ECE degree.

Transfer Credit

Students may petition to transfer a maximum of 15 graduate semester credits, with a grade of B or better, after they have enrolled in the degree program. This may be made up of a combination of up to 9 credits from the WPI ECE graduate courses taken prior to formal admission and up to 9 credits from other academic institutions. Transfer credit will not be allowed for undergraduate level courses taken at other institutions. In general, transfer credit will not be allowed for any WPI undergraduate courses used to fulfill undergraduate degree requirements; however note that there are exceptions in the case of students enrolled in the B.S./M.S. program.

Electrical and Computer Engineering Research Laboratories/Centers

Analog/Mixed Signal Microelectronics Laboratory

Prof. McNeill
The Analog and Mixed Signal Microelectronics Laboratory focuses on the continuation of research in self-calibrating analog to-digital converter architectures and low-jitter clock generation; funded by NSF, Allegro Microsystems, and Analog Devices. www.wpi.edu/+ECE

Bioelectromagnetics & Antenna Laboratory

Prof. Makaroff/Prof. Noetscher 
The Laboratory develops modeling and hardware design of various electronic systems and devices for biomedical (diagnostic and therapeutic) and wireless applications.

Bringing Awareness through Systems for Human Lab (BASH Lab)

Prof. Islam

At the Bringing Awareness through Systems for Humans (BASH) Lab, we are dedicated to pioneering AI-driven sensing technologies and mobile systems to enhance health, behavioral health, and various other application domains. Our research emphasizes the development of efficient and robust deep learning techniques for on-device applications and sustainable computing solutions. We also focus on AI for ambiently powered devices. Through an interdisciplinary approach spanning machine learning, mobile computing, embedded systems, and ubiquitous computing, we aim to create innovative solutions that address complex challenges and improve the quality of life across multiple fields.

Embedded Computer Laboratory

Prof. Huang
The mission of the Embedded Computing Lab is to solve important problems of embedded computer systems, including theories, architectures, circuits, and systems. Our current research is focused on ASIC, FPGA and SoC design for signal processing, wireless communications, error correction coding, reconfigurable computing, and computing acceleration. Our research goal is to create new architectures and circuit designs to facilitate high-speed information processing at minimum power consumption.
http://computing.wpi.edu/

Laboratory for Sensory and Physiologic Signal Processing – L(SP)2

Prof. Clancy
The mission of the Laboratory for Sensory and Physiologic Signal Processing L(SP)2 is to employ signal processing, mathematical modeling, and other electrical and computer engineering skills to study applications involving electromyography (EMG — the electrical activity of skeletal muscle). Researchers are improving the detection and interpretation of EMG for such uses as the control of powered prosthetic limbs, restoration of gait after stroke or traumatic brain injury, musculoskeletal modeling, and clinical/scientific assessment of neurologic function.
http://users.wpi.edu/~ted/

Center for Imaging and Sensing (CIS)

Prof. Ludwig
The lab has access to high-field and ultra high-field magnetic resonance imaging (MRI) systems for use in functional and anatomical imaging. Major research focuses on visualization of elastic vibrations in the female breast. A novel coil geometry was designed that proved more efficient at generating these strong gradients when compared with conventional coil technology. Research has resulted in the design of special-purpose radio frequency array coil systems for breast cancer diagnosis, bone density determin­ation, and stroke. The lab has successfully tested its single-tuned and dual-tuned prototypes at various sites throughout the U.S. in clinical MRI systems.
www.wpi.edu/+ECE
 

ICAS Lab

Prof. U. Guler
The research program of ICAS Lab explores the designs of a range of biomedical devices from implantable devices to wearable devices that ensure device security, personal privacy, accurate bio-sensing, and reliable operation and proposes possible directions of study that tackle the fundamental challenges including; sustainable energy harvesting systems for continuous long-term health monitoring (how sustainable energy harvesting and its efficient storage and usage are possible for continuous long-term personal health monitoring), secure bio-implants and wearables ( how the security of all these sensors associated with smart healthcare will be assured in terms of maintaining proper functionality of devices and protecting private information), and wireless sensor Interfaces for medical and general purpose IoTs (how accurate and reliable sensing interfaces will be able to receive very low-amplitude signals coming from various environments, such as inside the body). https://icaslab.org/

Signal Processing and Information Networking Laboratory (SPINLab)

Prof. Brown
SPINLab was established in 2002 to investigate fundamental and applied problems in signal processing, communi­cation systems, and networking. Our current focus is on the development of network carrier synchronization schemes to facilitate distributed beamforming and space-time coded cooperative transmission. We are also working on techniques for optimal resource allocation in multiuser communication systems and the application of game-theoretic tools to analyze selfish behavior in cooperative communication systems. SPINLab offers research opportunities at both the graduate and undergraduate levels. For more details, please see the SPINLab Web page at http://spinlab.wpi.edu.

Vernam Laboratory

Profs. Ganji, Schaumont, Sunar, Tajik, Martin (Mathematics), Mus

Computer chips bring unprecedented intelligence and support in every aspect of modern society including healthcare, intelligence, finance, transportation, and defense. Coupled with this convenience, these chips also bring unprecedented risk stemming from the sensitive information and their expected reliability. Vernam Lab addresses this risk by combining know-how from multiple relevant fields including hardware security, cryptography, and AI, to research and develop defenses and safeguards that minimize risk and mitigate threats to create a more secure and privacy-friendly future digitized world. https://vernamlab.org 

Wireless Innovation Laboratory (WILab)

Prof. Wyglinski
The Wireless Innovation Laboratory (WILab) conducts fundamental and applied research in wireless communication systems engineering and vehicular technology .  Consisting of approximately 1000 sq ft of prime research space as well as state-of-the-art software tool and experimentation equipment, this facility focuses on devising new real-world solutions and the creation of new knowledge in the areas of cognitive radio, rural broadband and the Digital Divide, connected and autonomous vehicles, software-defined radio, GPS and satellite communications, 4G/5G/6G/Next-G, spectrum sensing and co-existence, machine learning-based data transmission techniques, and millimeter wave transmission. WILab has been extensively funded via numerous sponsors from both government and industry, including the National Science Foundation, Verizon, MIT Lincoln Laboratory, MathWorks, Office of Naval Research, Toyota InfoTechnology Center USA, and the MITRE Corporation. For more details, please see the WILab website at http://www.Wireless.WPI.edu.

Electrical and Computer Engineering Courses by Area of Specialization and Delivery Mode