News Highlights

The latest updates and briefs from the Department of Electrical and Computing Engineering.

    Team Demonstrates Unconventional Approach to Solve Hard Computational Problems

    September 18, 2020

    Not all computing problems are created equal. Certain problems—commonly known as NP-hard problems—are considered intractable to solve using digital machines and require exponentially increasing resources for increasing sizes of the input. A team of electrical and computer engineers from the University of Virginia and Notre Dame demonstrate an unorthodox approach to help solve some of the toughest problems in computing. Published September 17 in Nature Communications, their paper, Using Synchronized Oscillators to Compute the Maximum Independent Set, presents an integrated circuit comprised of 30 oscillators that are able to synchronize with each other in highly reconfigurable patterns on a 1.44 square millimeter chip.

    Research Team’s Deep Learning Algorithms Facilitate Learning on Graph Data

    September 16, 2020

    Jundong Li, assistant professor of electrical and computer engineering at the University of Virginia, develops novel deep learning algorithms to glean more actionable patterns from graph-structured data sets. Li holds joint appointments in UVA’s Department of Computer Science and School of Data Science. Li and Shuiwang Ji, associate professor of computer science and engineering at Texas A&M, have earned a National Science Foundation grant to improve the essential building blocks of deep learning algorithms for graphs.

    Tensor Decomposition for Signal Processing and Machine Learning Is a Go-To Primer for Students and Practitioners

    September 02, 2020

    Each year, hundreds if not thousands of papers are published on tensor-related topics, easily overwhelming students and practitioners alike. Nikolaos Sidiropoulos, professor and chair of the Charles L. Brown department of electrical and computer engineering at the University of Virginia, led an effort to create an easy on-ramp for those eager to learn about and work with tensors. Sidiropoulos, a fellow of the Institute of Electrical and Electronics Engineers, collaborated with a small group of IEEE co-authors and other colleagues to publish Tensor Decomposition for Signal Processing and Machine Learning. The paper is ranked #1 in Google Scholar metrics for Transactions on Signal Processing, the flagship journal of the IEEE Signal Processing Society, for 2015-2020, and is the journal's most popular and frequently accessed paper in IEEE Xplore. It is recommended reading for anyone who needs to incorporate tensors in their research and algorithm development.

    Making the Pitch: Rapid-Relay Sensor System for Wildfire Warning

    August 12, 2020

    It’s said a picture is worth a thousand words. Jay Sheth’s vivid account of the Australian wildfires’ path of destruction made the case for rapid detection and response. Sheth described a dense network of reliable, inexpensive and self-powered detectors able to autonomously relay a fire warning in real time across thousands of square miles. His pitch earned first place at the IEEE Microwave Week three-minute thesis competition. Microwave Week celebrates the technical accomplishments of the top three conferences convened under the umbrella of the IEEE Microwave Theory and Techniques Society. The competition helps renew public interest in microwaves as a transformative—and potentially life-saving—technology. Sheth designed the power amplifiers for the ultra-low power transmitters as part of his dissertation research at the Integrated Electromagnetics, Circuits, and Systems lab led by Steven Bowers, assistant professor of electrical and computer engineering at the University of Virginia. Read the full story:

    New Research Partnership Explores Wireless Spectrum Sharing

    August 11, 2020

    The University of Virginia’s Charles L. Brown Department of Electrical and Computer Engineering is charting a path toward a vibrant future wireless environment compatible with both commercial applications and scientific research. A multi-institution research team is working to establish a center for Wireless Hardware Innovations and Signal Processing for Enhanced Radio-Astronomy and Scientific Spectrum Sharing, or WHISPERS. A planning grant from the National Science Foundation Spectrum Innovation Initiative supports their effort to address policy and technology challenges created by the worldwide growth of wireless systems and applications.

    WHISPERS leverages researchers’ expertise in design, metrology, detectors, devices and system hardware solutions that have advanced international scientific research operating in microwave to terahertz frequencies and beyond. The National Radio Astronomy Observatory, Northwestern University's McCormick School of Engineering and Virginia Diodes, Inc., have joined the WHISPERS partnership led by principal investigator Robert M. Weikle, II, University of Virginia professor of electrical and computer engineering. Read more.   

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    UVA Engineering Researchers Tackle Critical Challenge in Threat Detection for National and Homeland Defense

    July 21, 2020

    Two researchers in the University of Virginia’s Charles L. Brown Department of Electrical and Computer Engineering are applying machine learning and control theory to meet this need. Professors Scott Acton and Zongli Lin have earned a grant from the U.S. Army Research Office to tackle a long-standing challenge in intelligence, to keep eyes on an object that may change in appearance or may be temporarily hidden from view. Acton and Lin are developing a visual object tracking system that switches between automated and manual analysis to deliver the best results. READ MORE.

    New Bulk Data Transfer Method Achieves High Performance with Less Complexity

    July 21, 2020

    A team of computer engineers and computer scientists at Fuzhou University in China, Shanghai Jiao Tong University and @University of Virginia are helping organizations access networked data centers for fast decision-making and smooth operations. Their store-and-forward scheduling method temporarily stores bulk data that is not time-sensitive at intermediate sites and forwards the data when the network is less congested. In place of conventional scheduling that requires knowledge of the entire network, the team’s method reduces complexity and computing resources by relying on the status of a few pre-selected routes. They earned a best paper award for this research, presented at the Institute of Electrical and Electronics Engineers 2020 International Conference on High Performance Switching and Routing and published in the Journal of Optical and Communications Networking, Optical Switching and Networking. READ MORE.

    NASA Honors Ph.D. Graduate Harold Haldren

    June 26, 2020

    NASA honored Ph.D. graduate Harold Haldren (ECE ’20) and his adviser Mool Gupta, Langley Distinguished Professor of electrical and computer engineering at the University of Virginia, who earned second place in the 2020 H.J.E. Reid award competition. The Reid award is the highest recognition for a scientific research publication authored by those who support space mission projects at the NASA Langley Research Center. Daniel Perey, William Yost and Elliott Cramer, who lead research projects and programs for NASA Langley’s Nondestructive Evaluation Services Branch, join Haldren and Gupta as co-authors. The team’s paper, “Swept-Frequency Ultrasonic Phase Evaluation of Adhesive Bonding in Tri-layer Structures,” was published in the May 2019 issue of the Journal of the Acoustical Society of America. Read more.