Electrical and Computer Engineering Faculty

Ethan Ahn

Tama Moni — Thu, 03 Aug 2023 20:14:42 +0000

Ethan Ahn Tama Moni Thu, 08/03/2023 - 16:14

Associate Professor, Department of Electrical and Computer Engineering

Contact Information

Building: Nguyen Engineering

Email: eahn7@gmu.edu

Personal Websites

�鶹��Ƶ Nanoelectronics Lab

In the News

NSF grant supports nanofabrication workforce training
September 14, 2025
Small prints with big impact
February 3, 2025
New �鶹��Ƶ Nanofabrication Facility will help drive innovation in the commonwealth
January 17, 2024

Biography

Ethan Ahn is currently an associate professor of Electrical Engineering (EE) at �鶹��Ƶ. Previously, he served as an assistant (2016-2022) and associate (2022-2023) professor at the University of Texas at San Antonio, a senior panel process engineer at Apple, and a post-doctoral researcher at Stanford University. He received his PhD in EE at Stanford University in 2015 under the supervision of Prof. H.-S. Philip Wong. He worked as a spintronics research scientist at the Korea Institute of Science and Technology (KIST) from 2007-2010.

Ahn received the BS and MS degrees in EE from the Korea Advanced Institute of Science and Technology (KAIST) in Daejeon, Korea, in 2005 and 2007, respectively. He is the author of over 80 peer-reviewed research products. He has been the recipient of numerous awards of over $4M, including the prestigious AFOSR grant in Quantum Electronic Solids and the NSF EAGER grant in Electronics, Photonics, and Magnetic Devices (2019). He previously served on the technical committee of IEEE EDS Optoelectronic Devices and is currently serving as the editorial board member for Scientific Reports.

Degrees

PhD, Electrical Engineering, Stanford University (2015)

Aspiring to smoother traffic

tdonnel — Fri, 02 Jun 2023 19:19:23 +0000

Aspiring to smoother traffic tdonnel Fri, 06/02/2023 - 15:19

In This Story

Brian Mark

There are few better feelings than hitting all green lights on your drive home. Brian Mark’s research aims to bring you that feeling more often. Ideally, technology can help you hit a “green wave” by keeping your car within an optimal speed bracket, says �鶹��Ƶ electrical and computer engineering professor Brian Mark.

The increasing likelihood of autonomous vehicles on the road offers a prospect even more promising than the idea of creating an app for human drivers, originally proposed in joint work of Mark and Melvin Friedman, a retired physicist from the Army Night Vision and Electronic Sensors Directorate in Fort Belvoir, Virginia. Through �鶹��Ƶ's Office of Technology Transfer, Friedman and Mark submitted a U.S. patent application on a method for coordinating traffic lights and reducing traffic congestion.

“It probably will work even better with connected and automated vehicles,” explains Mark, “so you know the car itself is programmed to keep on the green wave. Like, if you have to turn right, you might not be on the green wave; so ... you might have to catch up to the green wave ahead of you or slow down to catch the green wave behind you.”

Mark supervised a senior design project to move toward his goal sponsored by the Army Strategic Program for Innovation, Research, and Employment (ASPIRE). Three George �鶹��Ƶ Electrical and Computer Engineering Department teams participated in ASPIRE, supervised by Qilian Li, Brian Mark, and Cameron Nowzari, respectively. As part of the program, in addition to several Zoom meetings, the seniors attended a spring meeting at Fort Belvoir, Virginia, where they presented their project progress.

Mark’s ASPIRE team constructed a model of a connected and automated vehicle. Sara Sulaiman Alaraini, Colin Graves, Corey Jones, Nitin Mandadi, Andrew Mokhtare, and Adham Obeid modified a remote-control vehicle to operate autonomously on a tarp designed like a road system, complete with centralized traffic light–controlled intersections. The team outfitted the car with sensors, a camera, and arUco tags to help it stay oriented in its environment.

"The traffic lights are connected to a centralized server, and the car is able to automatically stop at a traffic light and then go when it turns green,” said Mark.

“Through the centralized server you can indicate the destination ... It will automatically calculate the path through the street grid, and the car will just go to that destination and obey all the traffic lights as it goes.”

Mark hopes a future senior design team can further extend the project by incorporating multiple cars to simulate traffic scenarios.

“The next project would be if you have a bunch of cars. And they're all following green waves, so that they're all obeying the traffic lights. But they never really have to stop unless they have to turn. That would be the ultimate demonstration of this concept.”

Topics

Electrical and Computer Engineering

Electrical and Computer Engineering Faculty

Autonomous Cars

robotics and autonomous systems

�鶹��Ƶ Autonomy and Robotics Center

Research

patent

Missy Cummings

Tama Moni — Thu, 11 Aug 2022 15:29:20 +0000

Missy Cummings Tama Moni Thu, 08/11/2022 - 11:29

Professor and Director of �鶹��Ƶ Autonomy and Robotics Center (MARC); First American Bank Chair

Contact Information

Office: Engineering 2705
Phone: 703-993-6969
Email: cummings@gmu.edu

Personal Websites

Publications

In the News

�鶹��Ƶ's new MARC focuses on autonomy, robotics, and responsible AI
April 16, 2024
New certificate program in responsible AI starting fall 2024
March 1, 2024
College of Engineering and Computing launches graduate certificate programs in AI, microfabriction, smart grid technology, and machine learning
February 29, 2024
Associated Press: Missy Cummings (CEC) quoted in story about Pentagon AI initiatives
November 27, 2023
AI's future discussed at roundtable
June 13, 2023

Biography

As one of the U.S. Navy’s first female fighter pilots and an engineer, Mary “Missy” Cummings is accustomed to breaking barriers and solving problems.

A naval officer and military pilot from 1988-1999, Cummings was one of the U.S. Navy's first female fighter pilots. She is now the director of �鶹��Ƶ's Autonomy and Robotics Center (MARC) and a professor at �鶹��Ƶ. She holds faculty appointments in the Mechanical Engineering, Electrical and Computer Engineering, and Computer Science departments. She is an American Institute of Aeronautics and Astronautics (AIAA) Fellow and recently served as the senior safety advisor to the National Highway Traffic Safety Administration.

Cummings received her BS in Mathematics from the U.S. Naval Academy in 1988, her MS in Space Systems Engineering from the Naval Postgraduate School in 1994, and her PhD in Systems Engineering from the University of Virginia in 2004.

ORCID: 0000-0003-2557-6930

Degrees

BS, Mathematics, U.S. Naval Academy
MS, Space Systems Engineering, Naval Post Graduate School
PhD, Systems Engineering, University of Virginia

Research Interests

Human-unmanned Vehicle Interaction
Human-autonomous System Collaboration
Human-systems Engineering
Public Policy Implications of Unmanned Vehicles
Ethical and Social Impact of Technology

Filipe Veiga

Tama Moni — Wed, 10 Aug 2022 16:53:41 +0000

Filipe Veiga Tama Moni Wed, 08/10/2022 - 12:53

Assistant Professor, Department of Electrical and Computer Engineering

Contact Information

Phone: 703-993-1594

Campus: Fairfax

Building: Nguyen Engineering Building, Room 3253

Mail Stop: 1G5

Email: ffveiga@gmu.edu

Biography

Filipe Veiga is an assistant professor in the Department of Electrical and Computer Engineering at �鶹��Ƶ. He obtained his PhD in Machine Learning and Robotics from the Technische Universität Darmstadt after getting an MSc in Electrical and Computer Engineering from Instituto Superior Técnico. Prior to his appointment at �鶹��Ƶ, he was a postdoctoral associate at the Massachusetts Institute of Technology.

Filipe's research interests focus on the use of perception for the development of intelligent behavior in robots. He relies on biomimetic control approaches in conjunction with state-of-the-art machine learning and hierarchical and distributed systems in order to learn real-time state estimators and complex controllers. He investigates these topics in the context of robot manipulation and multi-model perception.

Degrees

PhD, Machine Learning and Robotics, Technische Universität Darmstadt
MSc, Electrical and Computer Engineering, Insituto Superior Técnico
BS, Engineering Sciences, Instituto Superior Técnico

Research Interests

Perception
Tactile sensing
Robotic manipulation

Publications

Google Scholar

Xuan Wang

Taylor Nguyen — Sat, 06 Nov 2021 22:28:43 +0000

Xuan Wang Taylor Nguyen Sat, 11/06/2021 - 18:28

Assistant Professor, Department of Electrical and Computer Engineering

Contact Information

Campus: Fairfax

Building: Nguyen Engineering Building

Room 3230

Mail Stop: 1G5

Email: xwang64@gmu.edu

In the News

Teaching humans to play safe
March 4, 2024

Personal Websites

Personal Website

Biography

Xuan Wang is an assistant professor in the Department of Electrical and Computer Engineering at �鶹��Ƶ. He received his PhD degree in autonomy and control, from the School of Aeronautics and Astronautics, Purdue University in 2020. After graduation, he worked as a post-doctoral researcher at the University of California, San Diego.

Dr. Wang’s search interests lie primarily in the autonomy and control of large-scale network systems, to improve their reliability, efficiency, security, and scalability. His current project topics include Multi-agent control and optimization; Resilient multi-agent coordination; System identification and data-driven control of neuron network systems. These topics have extensive applications in mobile sensor networks, smart cities, autonomous robot swarms, and the Internet of Things.

One of his papers received the ICPS 2021 Best Paper Award.

Degrees

PhD, Aeronautics and Astronautics, Purdue University
MSc, Control Science and Engineering, Harbin Institute of Technology
BSc, Automation, Harbin Institute of Technology

Research Interests

Distributed learning for MAS
Resilient multi-robot systems
Distributed resource allocation
Human-in-the-loop for MAS

Publications

Google Scholar

Tolga Soyata

Taylor Nguyen — Thu, 15 Jul 2021 02:16:46 +0000

Tolga Soyata Taylor Nguyen Wed, 07/14/2021 - 22:16

Professor, Department of Electrical and Computer Engineering

Contact Information

Phone: 703-993-5459
Campus: Fairfax
Building: Nguyen Engineering Building
Room 3228
Mail Stop: 1G5
Email: tsoyata@gmu.edu

Personal Websites

Personal Website

In the News

Amazon develops data center engineering curriculum with �鶹��Ƶ
July 27, 2023

Biography

Tolga Soyata received his BS in Electrical and Communications Engineering from Istanbul Technical University in 1988, MS in Electrical and Computer Engineering from Johns Hopkins University in 1992, and PhD in Electrical and Computer Engineering from the University of Rochester in 2000. He was an assistant research professor at the University of Rochester ECE Department between 2008 and 2016 and an associate professor at SUNY Albany ECE between 2016 and 2019. He was a senior lecturer at Johns Hopkins University ECE Department in 2020 before joining �鶹��Ƶ as an associate professor in 2021. His teaching interests include computer architecture, CMOS VLSI ASIC design, FPGA-based system design, and GPU architecture and programming. He has authored two books as well as two dozen journals and 30 conference papers, primarily in ACM and IEEE. His research interests include cyber-physical systems, digital health, and FPGA- and GPU-based high-performance computing. He is a senior member of both IEEE and ACM.

Degrees

PhD, Electrical and Computer Engineering, University of Rochester
MS, Electrical and Computer Engineering, Johns Hopkins University
BS, Electrical and Communications Engineering, Istanbul Technical University

Research Interests

Computer architecture
CMOS VLSI ASIC design,
FPGA-based system design
GPU architecture and programming

Publications

Google Scholar

Maryam Parsa

Taylor Nguyen — Thu, 15 Jul 2021 01:53:35 +0000

Maryam Parsa Taylor Nguyen Wed, 07/14/2021 - 21:53

Tenure-Track Assistant Professor, Department of Electrical and Computer Engineering; CEIE Affiliate Faculty

Contact Information

Phone: 703-993-6097
Campus: Fairfax
Building: Nguyen Engineering Building
Room 3215
Mail Stop: 1G5
Email: mparsa@gmu.edu

Personal Websites

Personal Website

In the News

Brainpower inspires energy-efficient AI
January 22, 2026
PhD student knows how to (neural) network
October 15, 2024
College of Engineering and Computing launches graduate certificate programs in AI, microfabriction, smart grid technology, and machine learning
February 29, 2024
Parsa joins three-year, $2.4 million 3D chip creation project
November 10, 2023

Biography

Maryam Parsa is an assistant professor in the Electrical and Computer Engineering department at �鶹��Ƶ. Prior to joining �鶹��Ƶ, she was a postdoctoral researcher at Oak Ridge National Laboratory in the Beyond Moore Computing group. She received her PhD in electrical and computer engineering from the Center for Brain-Inspired Computing (C-BRIC) at Purdue University in December 2020 with a prestigious four-year Intel Corporation and Semiconductor Research Corporation (SRC) PhD fellowship.

Parsa has broad interests in the areas of neuromorphic computing, neural architecture search, and Bayesian optimization across the full stack of materials, devices, circuits, systems, algorithms, and applications. Her research involves developing causal and physics-based machine learning and Bayesian optimization to accelerate materials discovery. Further, in her focus on neuromorphic computing, her goal is to not only enable accurate, fast, energy-efficient, and resilient intelligence at the edge through algorithm-hardware codesign but also to develop novel hierarchical learning/training approaches based on Bayesian optimization, evolutionary optimization, and synaptic learning rules. She is interested in a wide range of applications such as computational neuroscience, smart healthcare diagnosis, and cyber-physical systems.

Degrees

PhD, Electrical and Computer Engineering, Purdue University
MS, Civil Engineering, Purdue University
MS, Electrical and Computer Engineering, University of Ottawa
BS, Electrical and Computer Engineering, Khaje Nasir Toosi University of Technology

Research Interests

Neuromorphic learning
Bio-inspired robotics
Distributed learning
Algorithm hardware co-design

Publications

Google Scholar

Ningshi Yao

Taylor Nguyen — Sat, 03 Jul 2021 02:26:16 +0000

Ningshi Yao Taylor Nguyen Fri, 07/02/2021 - 22:26

Assistant Professor, Department of Electrical and Computer Engineering

Contact Information

Phone: 703-993-5599
Campus: Fairfax
Building: Research Hall
Room 166
Mail Stop: 1G5
Email: nyao4@gmu.edu

In the News

�鶹��Ƶ engineering professor awarded Office of Naval Research grant to launch 'NEXT' mechatronics workforce program
March 20, 2026
Engineering better vision: George �鶹��Ƶ professors lead $1.17M NIH project
July 30, 2025
George �鶹��Ƶ launches Virginia’s first robotics PhD
July 22, 2025
Sea life defended the republic
April 29, 2025
�鶹��Ƶ wins Defend the Republic
May 22, 2023

Personal Websites

Ciao Lab

Biography

Ningshi Yao is an assistant professor in the Department of Electrical and Computer Engineering at �鶹��Ƶ. She received her PhD from the School of Electrical and Computer Engineering at Georgia Institute of Technology in 2020, and her BS in Automatic Control from Zhejiang University, China, in 2014. Prior to joining �鶹��Ƶ, she was a postdoctoral research fellow at the Georgia Institute of Technology from November 2020 to July 2021.

In her research, she developed a novel contention-resolving model predictive control method to co-design scheduling and control for resource-constrained systems, such as networked control systems, traffic intersection management, and human-robot collaborative systems. Her research interests include real-time scheduling, control theory, cyber-physical systems, machine learning, and human-robot interaction.

Degrees

PhD, Electrical and Computer Engineering, Georgia Institute of Engineering
MS, Electrical and Computer Engineering, Georgia Institute of Engineering
BS, Automatic Control, Zhejiang University

Research Interests

Human-robot interactions
Human-robot co-learning
Bio-inspired robotics
Distributed resource allocation

Publications

Google Scholar

Research Spotlight

Ningshi Yao's work centers around control systems and human-robot interaction. She studies how robotic devices detect and adapt to human interaction. At �鶹��Ƶ, she works with faculty and students to create lighter-than-air autonomous balloons – "blimps" – that respond quickly and efficiently to various situations. Learn more about how these blimps work in the video below.

Weiwen Jiang

Taylor Nguyen — Sat, 03 Jul 2021 01:07:14 +0000

Weiwen Jiang Taylor Nguyen Fri, 07/02/2021 - 21:07

Tenure-track Assistant Professor, Department of Electrical and Computer Engineering

Contact Information

Campus: Fairfax
Building: Nguyen Engineering Building
Room 3247
Mail Stop: 1G5
Phone: (703)-993-5083
Email: wjiang8@gmu.edu

In the News

George �鶹��Ƶ researcher gets CAREER award for quantum leaps in computing, with the help of AI
February 13, 2025
Quantum conundrums: Navigating noise and enhancing expertise
August 23, 2023
Weiwen Jiang wins IEEE Best Paper Award
December 13, 2021

Personal Websites

Lab Website

Biography

Weiwen Jiang joined �鶹��Ƶ in 2021. Prior to this, he was a post-doctoral research associate at the University of Notre Dame. He received his PhD from Chongqing University in 2019. From 2017 to 2019, he conducted research at the University of Pittsburgh and was co-advised by the professor there for his PhD thesis. He works on Quantum Computing, AI Accelerators, and Hardware-Software Co-Design.

Jiang has published more than 80 research articles in refereed international conferences and premier journals, including 10+ IEEE/ACM Transactions papers. He is the recipient of the NSF CAREER AWARD 2025, ACM Sigda Meritorious Service Award 2024, the Best Paper Award in IEEE QuantumWeek 2023, IEEE TCAD 2021, NVMSA’15 and ICCD’17, the Best Paper Nomination in ASP-DAC’16, DAC’19, CODES+ISSS’19, and ASP-DAC’20 Best Poster Award in ORNL’s Quantum Computing User Forum 2023, First Place of the 31st ACM SIGDA University Demonstration at DAC 2021, Second Place of the 32nd ACM SIGDA University Demonstration at DAC 2022, and Top Winning Awards at IEEE Services Hackathon 2020. His works are supported by variance funding sources including NSF, DoE, ARO, Meta, and Leidos.

Jiang served as the Technical Track Co-Chair at IEEE QuantumWeek (2023-2025) Associate Editor at IEEE Transactions on Circuits and Systems - II: Express Briefs (2022-2023). He created the Quantum System Stability and Reproducibility Workshop (StableQ) and Tiny and Fair ML Design Competition at IEEE/ACM ESWEEK 2023.

Degrees

PhD, Computer Science, Chongqing University
Joint PhD, Electrical and Computer Engineering, University of Pittsburgh

Sai Manoj Pudukotai Dinakarrao

Martha Bushong — Sun, 09 Feb 2020 03:41:30 +0000

Sai Manoj Pudukotai Dinakarrao Martha Bushong Sat, 02/08/2020 - 22:41

Assistant Professor, Department of Electrical and Computer Engineering

Contact Information

Phone: 703-993-5083
Campus: Fairfax
Building: Nguyen Engineering Building
Room 3247

Email: spudukot@gmu.edu

Personal Websites

Personal Website

ORCID PROFILE

Biography

Sai Manoj Pudukotai Dinakarrao, an assistant professor in the Department of Electrical and Computer Engineering at �鶹��Ƶ, received a BTech degree in electronics and communication engineering from the Jawaharlal Nehru Technological University, Anantapur, India, in 2010; an MTech in information technology with a specialization in networking and communication from International Institute of Information Technology Bangalore, India, in 2012; and PhD degree in electrical engineering from the Nanyang Technological University, Singapore in 2015. He worked as a post-doctoral researcher at TU Wien in Vienna, Austria, between 2015 and 2017. He worked as a post-doctoral researcher and research assistant professor at �鶹��Ƶ in 2017 and 2018.

Pudukotai Dinakarrao’s research interests include hardware security, adversarial machine learning, Internet of Things networks, deep learning in resource-constrained environments, in-memory computing, accelerator design, algorithms, design of self-aware many-core microprocessors, and resource management in many-core microprocessors. He was a recipient of The Young Research Fellow Award in the Design Automation Conference (DAC) 2013. His student won the Xilinx Open Hardware Contest 2017 (Student Category).

His works won best paper awards in top-tier conferences like ICDM and ICCE and were also nominated for best paper awards in conferences like DATE and ICCAD.

Degrees

PhD, Electrical and Electronic Engineering, Nanyang Technological University
MTech, Information Technology, International Institute of Information Technology Bangalore
BTech, Electronics and Communication Engineering, Jawaharlal Nehru Technological University, Anantapur