NIPS Conference 2017 showcases work from DAC Ph.D. students













A group of Ph.D. students from the Discovery Analytics Center headed with their faculty advisors to Long Beach, California, last week to present papers and posters at the 2017 Conference on Neural Information Processing Systems (NIPS). One of the workshop papers was distinguished with a Best Paper Award and two of the students received NIPS Travel Awards.

2017 marks the 31st year for the international multi-track machine learning and computational neuroscience conference includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers, and workshops.

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The Discovery Analytics Center enhances strengths with four new faculty

Left to Right (top), Mark Embree, Tanushree Mitra; (bottom) Srijan Sengupta, Jia-Bin Huang

The Discovery Analytics Center welcomes four new faculty this fall who will help lead Virginia Tech’s big data research and education efforts on campus.

“Data analytics is inherently interdisciplinary and our new faculty bring expertise that will bolster our strengths in matrix computations, statistical methodology for network data, computer vision, and information credibility as we strive to find data solutions to modern problems,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science and director of the Discovery Analytics Center.

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DAC has strong presence at ICDM 2017

DAC Ph.D. student, Zhiqian Chen, presenting his paper at ICDM 2017.

The Discovery Analytics Center was strongly represented at the IEEE International Conference on Data Mining (ICDM) in New Orleans, Nov. 18-21, with a number of accepted research papers by DAC faculty and students and DAC faculty serving on committees and panels.

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Brian Goode recognized with Innovation Award from the Fragile Families Challenge

Brian Goode focused on data-driven and process-driven approaches to create predictive models for six outcomes of 4,242 participants. He presented his work at the Fragile Families Challenge Scientific Workshop at Princeton University last week. Click here to read more about Brian’s award.

Elaheh Raisi and Bert Huang awarded ACM/IEEE Best Paper Award at Sydney conference

Elaheh Raisi, a computer science Ph.D. student in the Discovery Analytics Center and her advisor, Bert Huang, assistant professor in the Department of Computer Science, were recently honored with the Best Paper Award at the 2017 IEEE/Association for Computing Machinery International Conference on Advances in Social Networks Analysis and Mining (ASONAM), in Sydney, Australia.

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Center for American Progress report cites Discovery Analytics Center collaboration with commonwealth of Virginia as example of improving workforce data

People walk through the Oculus at the World Trade Center in New York, June 16, 2017.

A Center for American Progress report on using open data standards to enhance the quality and availability of online job postings has highlighted the Gov. Terry McAuliffe’s Commonwealth Consortium for Advanced Research and Statistics (CCARS) and its work with the Discovery Analytics Center at Virginia Tech to develop the Open Data, Open Jobs Initiative. The goal of the pilot was to capture and publish a real-time structured data feed of all online job postings in Virginia that would serve as a proof of concept.

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DAC Ph.D. student Rupinder Paul Khandpur invited to speak at CyCon

 Rupinder Paul Khandpur, a DAC Ph.D student in computer science, was invited to speak to a group of analysts at the 2017 International Conference on Cyber Conflict (CyCon). The conference, held in Tallinn, Estonia, focused on the fundamental aspects of cyber security with a theme of Defending the Core.

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DAC and BI lead DARPA’s Next Generation Social Science Project

brian & Chris

Brian Goode (left), from the Discovery Analytics Center, and Chris Kuhlman, from the Biocomplexity Institute at Virginia Tech, collaborate on developing models for large-scale social behavior.

DAC and the Biocomplexity Institute are leading a $3 million grant awarded by the Defense Advanced Research Projects Agency (DARPA) as part of the Next Generation Social Science (NGS2) program.  DAC and BI will conduct research that will streamline modeling processes, experimental design, and methodology in the social sciences. A major objective of the project is to make social science experiments rigorous, reproducible, and scalable to large populations.

Graduate certificate in urban computing approved

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Left to right: Hesham Rakha and Huthaifa Ashqar work on a simulation of speed harmonization algorithm on I-66 using INTEGRATION; Scotland Leman and Matt Slifko discuss spatial relationships in the housing market.

New interdisciplinary certificate in urban computing, part of National Science Foundation (NSF) Research Traineeship UrbComp Program, is now available to all Virginia Tech graduate students. Administered through the Discovery Analytics Center, the 12-credit certificate program weaves interdisciplinary applications through new courses and a novel “tapestry” curriculum.

These courses are designed to train students to become competent problem solvers by developing computational models of urban populations from disparate data sources and posing and answering what-if questions via machine learning and visualization methodologies. Students are also trained in the ethical and professional implications of working with massive datasets.  Click here to read more about the certificate.

DAC Director Naren Ramakrishnan explores big data analytics to plan for smart cities


Naren Ramakrishnan, DAC director and professor of computer science.

DAC director, Naren Ramakrishnan, takes part in a VT Engineering team leading a three-year, $1.4 million National Science Foundation (NSF) grant to develop a new planning framework for smart, connected, and sustainable communities.  The team wants smart cities to features zero energy, zero outage, and zero congestion.  They are utilizing big data and interdisciplinary technology as tools to meet that goal.  Click here to read more about the project.