News Highlights

Yixin Sun Publishes Research on Detecting Malware Injection

Yixin Sun, Anita Jones Career Enhancement Assistant Professor of Computer Science and Electrical and Computer Engineering at the University of Virginia, joined university and industry researchers to develop a new approach to detect malware injection. Sun is first author on the team’s paper, published in the Proceedings of the 2020 IEEE European Symposium on Security and Privacy. The paper presents a new approach to effectively detect stealthy attacks from seemingly legitimate connections to popular web services made by benign programs.

The research team built a fine-grained Program-DNS profile for each benign program to characterize expected DNS behavior. From the Program-DNS profile, the team developed six novel features on a dataset of over 130 million DNS requests collected from a real-world enterprise and 8 million requests from malware-samples executed in a sandbox environment. Their novel features successfully detected 190 malware-injected processes that would have otherwise gone unnoticed. Their study demonstrates that fine-grained Program-DNS profiles can help detect attack campaigns that bypass traditional DNS monitoring safeguards and signature-based detection techniques. Read the paper: https://conferences.computer.org/eurosp/pdfs/EuroSP2020-2psedXWK6U4prXdo7t91Gm/508700a552/508700a552.pdf

Machine Learning Technique Promises Early Detection of Osteoarthritis

Gustavo Rohde, professor of biomedical engineering and electrical and computer engineering at the University of Virginia, is senior author of a collaborative research study in machine learning to identify patients vulnerable to osteoarthritis.

Deep Learning for Predictive Image Registration Promises Efficient Large-scale Image Analysis

Potential patient-care applications include radiotherapy planning, clinical studies of neurodegenerative diseases and real-time image-guided navigation for surgery.

Yixin Sun Gains Recognition through Privacy Enhancing Technologies Award Competition

Yixin Sun earned recognition for her outstanding contributions to the theory, design, implementation and deployment of privacy enhancing technologies. Sun, Anita Jones Career Enhancement Assistant Professor of Computer Science and Electrical and Computer Engineering at the University of Virginia, is the runner up in the 2020 Caspar Bowden Award competition. 

Georgios Bakirtzis Applies Research Fellowship to Make Cyber-Physical Systems More Safe and Secure

Congratulations to Georgios Bakirtzis, who has earned the James G. Simmonds Fellowship in Applied Mechanics and Applied Mathematics Research. Bakirtzis is a Ph.D. student in computer engineering at the University of Virginia.

Ph.D. Student Armita Salahi Applies Machine Learning to Improve Patient Outcomes from Chemotherapeutic Treatments

Armita Salahi has earned a Sture G. Olsson Fellowship to develop systems approaches in biomedical engineering. Salahi is a Ph.D. student of electrical engineering advised by Nathan Swami, professor of electrical and computer engineering at the University of Virginia. Salahi joined Swami’s lab in 2015 to pursue her interest in developing devices for disease diagnostics, earning her Master of Science degree within two years. To understand disease onset and progression, Salahi develops label-free microfluidic methods to measure and analyze the biophysical properties of single cells to characterize the role of heterogeneity in diseases. 

Cong Shen’s Trifecta of NSF Grants Accelerates Machine Learning in Wireless Communications

Cong Shen, assistant professor of electrical and computer engineering at the University of Virginia, has earned three grants from the National Science Foundation to meet rising demands on wireless networks and advance machine learning. Shen is an expert in machine learning for wireless networks who possesses extensive industry R&D experience and 17 U.S. patents in wireless communication and networking.

Shuo Li Provides Winning Answer to IEEE SSCS Challenge Problem

Congratulations to Shuo Li, winner of the IEEE SSCS International Student Circuit Contest. The contest engages undergraduate and graduate students in thought-provoking circuit analysis and design. Students were invited to provide an intuitive response to a challenge problem: a feedback amplifier that at first glance seems to be unstable but is perfectly stable. Li was one of two contestants whose explanation earned an award. Li is working toward his Ph.D. in electrical engineering in the Robust Low Power VLSI group led by Benton H. Calhoun, professor of electrical and computer engineering. Li’s research interests include analog/mixed-signal integrated circuit and system design, particularly in areas of energy-harvesting, DC-DC converters, sensor interfaces, and system-on-chips for ultra-low-power IoT applications. Learn more: https://sscs.ieee.org/education/2019-student-circuit-contest.

IEEE Signal Processing Society Launches PROGRESS, a Diversity and Inclusion Initiative

UVA electrical and computer engineers support the launch of PROGRESS, a diversity, equity and inclusion initiative of the IEEE Signal Processing Society. Nikos Sidiropoulos, Louis T. Rader Professor and department chair, serves on the 2020 PROGRESS oversight committee. PROGRESS aims to motivate and support women and under-represented minorities to pursue academic careers in signal processing. An inaugural PROGRESS workshop will be held Oct. 26-27 during the 2020 IEEE International Conference on Image Processing, to provide information, tools and networking opportunities. A similar workshop is planned for the IEEE 2021 International Conference on Acoustics, Speech and Signal Processing. Learn more about PROGRESS and apply to participate in the IEEE ICIP PROGRESS workshop: https://2020.ieeeicip.org/progress.

Team Demonstrates Unconventional Approach to Solve Hard Computational Problems

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.