DAC is home to high-profile research, garnering recognition within and beyond the data analytics community.
Our talented team has been recognized with many competitive research awards and featured in major news and media outlets such as the Wall Street Journal, Newsweek, the Boston Globe and the Chronicle of Higher Education.
DAC Ph.D. student Chidubem Arachie is working remotely as an intern at Google Research.
A national pandemic that forced the closing of physical offices has not stopped graduate students at the Discovery Analytics Center from working remote internships at companies, research laboratories, and other institutions across the country. For many students, summer internships help further their own research as they gain real world experience.
Following is a list of DAC students and the work they are doing for the next few months:
Chidubem Arachie, a Ph.D. student in computer science, is a research intern at Google Research in Mountain View California. He is working on generative modeling for 3D shapes. His advisor is Bert Huang.
Hongjie Chen, a Ph.D. student in computer science, is a data science research intern at Adobe in San Jose, California. He is on the Cloud Technology Team, researching cloud resource allocation strategy. His advisor is Hoda Eldardiry.
Clockwise from top left: UrbComp students Nikhil Muralidhar, Joshua Detwiler, Whitney Hayes, and Shane Bookhultz
Students in the urban computing graduate certificate program gave their group presentations via Zoom at the end of semester 2020 Spring Retreat, focusing on the very thing that led to this virtual format — COVID-19.
The students were charged with taking a look at the pandemic’s impact beyond health — such as economic outcomes, urban design, and interpersonal and online relationships — by Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science and director of the Discovery Analytics Center, which administers the National Science Foundation-sponsored multidisciplinary program. Click here to read more about the UrbComp Spring Retreat.
Among Virginia Tech graduates celebrating their achievements today include four Ph.D. and five master’s students at the Discovery Analytics Center.
Four Ph.D. students and one master’s student plan to complete degrees during the summer.
“The thoughtful and impactful research our students have engaged in while pursuing their graduate degrees has been recognized by many major academic conferences and is testament to their hard work,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and director of the center.
Gopikrishna Rathinavel, DAC M.S. student in the Department of Computer Science
Gopikrishna Rathinavel was introduced to machine learning through the biotechnology courses he took as an undergraduate.
“Eager to learn more, I began attending lectures by industry experts in machine learning,” Rathinavel said. “Soon I was captivated by the potential that machine learning offers as a discipline. It can add valuable insights in any domain where there is some data to exploit.”
Omer Zulfiqar, DAC master’s student in the Department of Computer Science.
Graphic is from the paper, “RIDE-SECURE: Metro Security Incidents And Threat Detection Using Social Media”
After raduating from Virginia Tech in December 2018 with a bachelor of science degree in electrical engineering and a minor in computer science, Omer Zulfiqar moved to northern Virginia to be closer to his family. He was also in close proximity to the university’s location in the greater Washington, D.C. area.
In Fall 2019, he began pursuing a master’s degree in computer science and once again, chose Virginia Tech, this time at the Falls Church campus.
“Virginia Tech is a world renowned university in the field and at the Discovery Analytics Center I am able to work on interdisciplinary collaborations guided by incredible faculty, like my advisor Dr. Chang-Tien Lu, who are doing some amazing research work in the fields of artificial intelligence, machine learning, and data mining,” Zulfiqar said.
“Algorithmic components developed by DAC will go into a high-performance pipeline that enables inspection of extracted patterns as well as the lineage of data transformations underlying the patterns,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and DAC director, who is the principal investigator for the project.
Andreea Sistrunk, DAC Ph.D. student in Department of Computer Science
Graphic is from the paper “REGAL: A regionalization framework for school boundaries”
When Andreea Sistrunk started taking classes at Virginia Tech in the fall of 2014 she had left her job as a full time teacher in northern Virginia to devote more time to her two young daughters, ages three and seven.
“It was becoming more difficult for me to hold a full time job and be a good mother so I chose to take a break from work,” Sistrunk said. “I used a sort of ‘mom’s night out’ to enroll in a graduate course at Virginia Tech because I really missed learning new things.”
Nikhil Muralidhar, DAC and UrbComp Ph.D. student in the Department of Computer Science
Graphic is from Muralidhar’s paper on “PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly”
Choosing to pursue a Ph.D. in computer science at Virginia Tech was easy for Nikhil Muralidhar.
“Virginia Tech was my top choice for good reason,” Muralidhar said. “It is known for its quality research and interdepartmental collaborations, for encouraging students to work on real world interdisciplinary applications, and for pioneering programs like UrbComp.”
“I had been following DAC’s track record of high quality, practical research since I was a Virginia Tech undergraduate. I am happy to be part of a rare breed of research labs with both extensive industrial and academic collaborations. The facilities are state-of-the-art and the faculty are approachable, helpful, and use their experience to guide their students to become successful researchers,” said Muralidhar, who is advised by Naren Ramakrishnan.
Lei Zhang, DAC Ph.D. student in the Department of Computer Science
Graphic is from Zhang’s research on “Situation-Based Interpretable Learning for Personality Prediction in Social Media”
Lei Zhang was a master’s degree student in software engineering at Jinan University in China when his advisor told him about meeting Chang-Tien Lu from Virginia Tech and how he was doing research with algorithms on Twitter. While they were using different platforms — Zhang’s own work was on Weibo, the largest Chinese microblogging website — he was interested to hear about Lu’s research.
When he decided to pursue a Ph.D., Zhang decided to apply to Virginia Tech’s Department of Computer Science. As it turned out, Lu is now his advisor.