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

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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

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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.


Coverage of DAC Ph.D. student Yaser Keneshloo’s research with Washington Post

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The summation chain around pulleys on Tide Predicting Machine No. 2.

Great coverage of DAC Ph.D. student Yaser Keneshloo’s research in collaboration with the Washington Post on applying data science to predict the popularity of news articles.  Keneshloo and the Post are working on a popularity prediction experiment, they are doing clickstream analysis and producing a pipeline for processing tens of millions of daily clicks, for thousands of articles. Click here to read more about Keneshloo’s project.

 

 


DAC faculty Chandan Reddy wins Best Student Paper at IEEE

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Chandan Reddy (left) and his collaborators from the the Korea University (right).

Congratulations to Chandan Reddy, DAC faculty member and associate professor of Virginia Tech – Computer Science, whose paper in collaboration with Korea University, Boosted L-EnsNMF: Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization, received the Best Student Paper Award at the IEEE Conference on Data Mining! Click here for a full list of awards.


DAC PhD student Saurav Ghosh published in Nature Scientific Reports

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Flow chart depicting the sequential modeling process of EpiNews

DAC PhD student Saurav Ghosh’s work was published in Nature Scientific Reports. His research explores relationships between news coverage and modeling of infectious disease outbreaks

The research is in collaboration with Boston Children’s Hospital and University of Washington, Seattle. Click here to read more about Ghosh’s research.


DAC director Naren Ramakrishnan receives grant from Army Research Lab

ece_article_161221_internet_of_battlefield_articleWalid Saad, assistant professor in electrical and computer engineering, and Naren Ramakrishnan, and professor of computer science and director of DAC, are leading a $324,000 U.S. Army Research Laboratory grant that is laying groundwork for the Internet of Battlefield Things.

They are developing a planning framework that would present mathematical tools to understand how to transform existing battlefield capabilities into a large-scale IoBT. Click here to read more about the project.