Congratulations to our Ph.D. and master’s degree Spring graduates at the Discovery Analytics Center!

DAC graduates include (left to right): Xuchao Zhang with advisor Chang-Tien Lu in the National Capital Region; and Elaheh Raisi with Bert Huang and Yufeng Ma hooded by Ed Fox, both in Blacksburg.

The Discovery Analytics Center is pleased to announce that five of their Ph.D. and four of their master’s degree students celebrated graduation from Virginia Tech last weekend at Commencement ceremonies in Blacksburg and in the National Capital Region.

“It is always bittersweet to bid our students farewell, but we wish them all the best. We know and appreciate how hard they have worked to achieve the high goals they set for themselves and look forward to following their successful careers in academia and industry,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and director of the center.

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DAC student Xinfeng Xu garners 2019 Computer Science MS Research Award

Xinfeng Xu, DAC Master’s student in computer science

Xinfeng Xu, a master’s student in the Discovery Analytics Center, received the Computer Science MS Research Award at the CS Awards Banquet last night.

The award recognizes the best MS thesis in CS with consideration to novelty of idea; quality of resulting publications; effectiveness of writing; and contributions/impact to the field overall.

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Amazon Research Award supports developing algorithms that tackle unfairness in recommendation engines

Bert Huang, DAC faculty member and assistant professor of computer science

Why would a recommendation engine not suggest computer science classes to a female college student interested in that field of study?

According to Bert Huang, assistant professor of computer science in the College of Engineering and a faculty member at the Discovery Analytics Center, there are a few reasons. The engine may have trained from data representing the existing gender imbalance in computer science, unfair patterns may have inadvertently emerged from the mathematical nature of its learning algorithm and model, or there may be a less-visible or harder-to-detect process in place.  Click here to read more about Bert’s work.

Software platform engages communities in school rezoning decisions

Left to right: Colin Flynn, Vicki Keegan, and Susan Hembach from Loudoun County Public Schools meet at the Discovery Analytics Center with Ph.D. students Andreea Sistrunk, Subhodip Biswas, and Fanglan Chen to discuss how Redistrict is helping to establish school attendance zones.

School rezoning decisions often cause emotional stress for families and communities for a variety of reasons.

Parents worry about continuity of programs and activities at a new school, the toll it might take on their children’s friendships, and modes of transportation. School officials, administrators, and staff want to ensure that all students have equitable access to educational programs and facilities. Almost everyone is concerned about the impact a particular school attendance zone will have on traffic patterns, especially at opening and closing times.

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DAC Student Spotlight: Payel Bandyopadhyay

Payel Bandyopadhyay, DAC Ph.D. student computer science

Payel Bandyopadhyay is trying to understand the role of 3D immersive environment (an artificial, interactive, computer-created scene or “world” within which a user can immerse themselves) for sensemaking in textual data.

According to Bandyopadhyay, prior work at Virginia Tech by her advisor Chris North and others has shown the part that 2D space plays in sensemaking. Her current research investigates 3D immersive environments to determine if they provide any additional benefit or not.

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DAC Student Spotlight: Lulwah AlKulaib

Lulwah AlKulaib, DAC Ph.D. student in computer science

While a master’s degree student in computer science at George Washington University, Lulwah AlKulaib would look for published papers in high impact factor journals and highly respected, top rated conferences matching her field of interest, machine learning.

“This is where I first learned about the Discovery Analytics Center, the research being done there, and that it was located in northern Virginia as well as in Blacksburg,” she said.

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Discovery Analytics Center study sheds light on what turns a peaceful protest into a violent one

Protest in Brazil

Protests are an increasingly common occurrence, but only a small percentage of them turn violent. In a collaborative study led by the Discovery Analytics Center with the University of California, San Diego, and George Mason University, a team of researchers set out to uncover triggers that foretell violence by crowds.

Gathering data from thousands of online news sources in five Latin American countries — Argentina, Brazil, Colombia, Paraguay, and Venezuela — the researchers used the characteristics of past events to develop new methods that forecast the occurrence of violent crowd behavior in advance.

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DAC Student Spotlight: Tyler Chang

Tyler Chang, DAC Ph.D. student in computer science

The spring semester has brought some good news for Tyler Chang, a Ph.D. student at the Discovery Analytics Center.  In June, he will begin a six-month appointment at Argonne National Lab in Washington, D.C., where he will continue to work on his dissertation while applying his work to a new set of problems relevant to the U.S. Department of Energy.

Chang, a computer science major specializing in numerical analysis, is focusing his research on interpolation and nonconvex optimization.  His advisor is Layne Watson.

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Winning Blockchain Challenge team includes DAC student Arjun Choudhry

From left to right: Ikechukwu Dimobi, Arjun Choudhry, and Zachary Gould

A three-member student-driven team that includes Arjun Choudhry, a student at the Discovery Analytics Center, has won first place in the design phase of the Virginia Tech Blockchain Challenge led by the Department of Computer Science and made possible in part through a generous gift from, a leader in providing high-performance blockchain solutions. The award carries a $1,000 prize.

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DAC Student Spotlight: Shuo Lei

Shuo Lei, DAC Ph.D. student in computer science

A Ph.D. student in computer science, Shuo Lei is focusing her research on few-shot learning and robust model learning. She is advised by Chang-Tien Lu.

“The aim of AI is to train machines to do some of the work that people were needed to do previously,” said Lei. “The training process requires a large amount of labeled data. It is time intensive and there are significant labor costs in collecting and labeling all that data. Few-shot learning can be valuable in forwarding research because it reduces the training cost by using less labeled data to get the same – and sometimes even greater – accuracy in training results.

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