News

The prospect of being located in the heart of Northern Virginia drew Rongrong Tao to Virginia Tech and the Discovery Analytics Center in the National Capital Region. A Ph.D. student who earned a master’s degree in computer science at the University of Michigan in Ann Arbor, Tao conducts research on misinformation detection and analysis.

“This location provides opportunities for collaboration with academic institutes in the metropolitan D.C. area and an advantage for future career advancement,” said Tao. After graduation, she would like to work in an industry where she can apply data mining techniques to real-world problems.

Continue reading…

Ellis Kessler graduated from Virginia Tech in the spring of 2017 with a bachelor’s degree in mechanical engineering. The following fall, he was back at the university working toward a Ph.D.

“As an undergraduate, I knew I wanted to do some kind of research with vibrations or structural dynamics. My adviser, Pablo Tarazaga, taught about vibrations and by working with him in the Virginia Tech Smart Infrastructure Laboratory, I became involved with vibrations research on the Goodwin Hall building,” Kessler said.

Continue reading…

Jonathan Baker and Sirui Yao, Ph.D. students at the Discovery Analytics Center, and Leanna Ireland, a National Science Foundation research trainee in the Urban Computing (UrbComp) Certificate program administered through DAC, have each been awarded a Deloitte Foundation Data Analytics Fellowship in the amount of $10,000 to fund their research.

Baker, also a National Science Foundation research trainee in the UrbComp program, is a math major advised by Mark Embree, professor of mathematics, associate director of the Virginia Tech Smart Infrastructure Laboratory, and DAC faculty.

Yao is a computer science major advised by Bert Huang, assistant professor of computer science and DAC faculty.

Leanna Ireland, a sociology major, is advised by James Hawdon, professor and director of the Center for Peace Studies.

Continue reading…

In his research, Kaiqun Fu uses spatial data mining, urban computing, and machine learning to infer crime rates/types from street view images, roadway networks, and criminal records. Applying deep learning methods also uncover hidden safety-related patterns from the physical appearance of street blocks that help address urban safety issues.

Continue reading…

Sorour Ekhtiari Amiri developed an interest in machine learning during her senior year of college. After earning a bachelor’s degree in computer engineering from Beheshti University, she worked on machine learning applications while getting a master’s in computer engineering at the University of Tehran.

Amiri then decided to pursue a Ph.D. in computer science.

Continue reading…

Yuliang Zou, a Ph.D. student at the Discovery Analytics Center, was in Munich, Germany, earlier this week to participate in the 2018 European Conference on Computer Vision ECCV.  The conference, held every other year, is one of the most influential academic conferences for this area of research.

Continue reading…

It is no coincidence that Matthew Slifko’s research in predictive modeling in the presence of big and/or messy data deals specifically with the real estate market.

“As I prepared to return to grad school in July 2013, I was selling the house that I had bought at the beginning of the housing bubble in 2008,” said Slifko. “While predictive modeling had always been a favorite topic of mine as a student, real estate was a personal interest before it became an academic one.”

Continue reading…

As a computer science student at the American University of Nigera, Chidubem Arachie had spent a year as an exchange student at American University in Washington, D.C. Back in Nigeria, he graduated, taught high school math and computer science as a corpsman in the National Youth Services Corp in Lagos for a year and worked just shy of two years as a tax accountant at KPMG Nigeria.

Continue reading…

A collaborative project with the Washington Post to predict the popularity of news articles kept Yaser Keneshloo busy after joining the Discovery Analytics Center in the spring semester of 2014.

“The Washington Post now uses this research as an internal tool for predicting the click-rate of a news article within 24 hours of publication,” said Keneshloo, who worked on this project with his advisor, Naren Ramakrishnan. He has also presented this work at the 2016 SIAM International Conference in a publication co-authored with his Washington Post collaborators.

Continue reading…

Chandan Reddy, an associate professor in computer science and a faculty member at the Discovery Analytics Center, has received a Criteo Faculty Research Award from the Criteo AI Lab.

This grant allows Reddy and his students to develop new computational techniques for some of the challenging problems that arise in the domain of computational advertising. Specifically, Reddy’s lab will be working on building deep learning based methods for the problem of identifying potential customers interested in a particular product based on the past activities in the entire customer pool. Deep learning is an important subfield of artificial intelligence.

Continue reading…