Department News

Syndicate content
CS@VT
Updated: 52 min 56 sec ago

Smartwatch app could inspire more frequent physical activity, Virginia Tech study finds

Fri, 2017-08-25 15:35

An interdisciplinary study conducted by researchers at Virginia Tech suggests the secret to obtaining your summertime fitness goals might not be the amount of weight you’re bench pressing or how many miles you run, but generating friendly competition to keep you one step ahead of your fitness buddies.

The concept of friendly competition in group exercise being explored by the researchers uses a smartwatch app that could help people in a group exercise program get —and stay — more active.

At the heart of the group exercise research is a Fitbit-like smartwatch and its software developed by Andrey Esakia, a Ph.D. candidate in Virginia Tech’s Department of Computer Science who worked on the project to study the effects of technology in group physical activity. The work is supported by a multidisciplinary seed grant from Virginia Tech’s Institute for Creativity, Arts, and Technology.

Esakia collaborated with the Department of Human Nutrition, Foods, and Exercise in the College of Agriculture and Life Sciences and the Department of Communication in the College of Liberal Arts and Human Sciences to incorporate the hardware and software of the watch into an existing initiative, FitEx, from the Physical Activity Leadership Team of Virginia Cooperative Extension and the Physical Activity Research and Community Implementation Laboratory. FitEx is an eight-week physical activity and fruit and vegetable consumption program delivered in community settings.

 

Read more

Overlap in computer modeling holds key to next-generation processing, Virginia Tech researchers find

Tue, 2017-06-20 14:48

Exascale computing — the ability to perform calculations at 1 billion billion per second — is what researchers are striving to push processors to do in the next decade. That’s 1,000 times faster than the first petascale computer that came into existence in 2008.

Achieving efficiency will be paramount to building high-performance parallel computing systems if applications are to run in environments of enormous scale and also limited power.

A team of researchers in the Department of Computer Science in Virginia Tech’s College of Engineering discovered a key to what could keep supercomputing on the road to the ever-faster processing times needed to achieve exascale computing — and what policymakers say is necessary to keep the United States competitive in industries from everything to cybersecurity to ecommerce.

“Parallel computing is everywhere when you think about it,”said Bo Li, computer science Ph.D. candidate and first author on the paper being presented about the team’s research this month. “From making Hollywood movies to managing cybersecurity threats to contributing to milestones in life science research, making strides in processing times is a priority to get to the next generation of supercomputing.”

Li will present the team’s research on June 29 at the Association for Computing Machinery’s 26th International Symposium on High Performance Parallel and Distributed Computing in Washington, D.C. The research was funded by the National Science Foundation.

 

Read More

 

Daphne Yao receives $1.2 million Office of Naval Research (ONR) grant

Mon, 2017-05-22 16:51

Daphne Yao, an associate professor of computer science, is the principle investigator on a new three-year $1.2 million Office of Naval Research (ONR) grant, title “Data-driven Vulnerability Repair in Programs with a Cloud Analytics Architecture for Practical Deployment.” Na Meng, computer science assistant professor, and Trent Jaeger, computer science professor at Penn State University, are co-principle investigators on the grant. Yao is also the Elizabeth and James E. Turner Jr. ’56 and L-3  Fellow.

Abstract: The proposed effort is toward a secure software ecosystem that enables the automatic attack detection, vulnerability localization, code repair against attacks including stealthy exploits. In this project, we will focus on vulnerability location and code repair that leverage and build upon existing security detection solutions, i.e., detection-guided localization and repair. In preparation for near-term deployment, we will also develop a new cloud data analytics framework that minimizes the client-side effort and substantially enhances the transparency and usability of data-driven security tools. Danfeng Yao

 

Na Meng