Chandan Reddy

Chandan Reddy is an associate professor in the Department of Computer Science at Virginia Tech. He received his Ph.D. from Cornell University and an M.S. from Michigan State University. His primary research interests are data mining and machine learning with applications to healthcare analytics, bioinformatics, and social network analysis.

Reddy’s research is funded by the National Science Foundation, the National Institutes of Health, the Department of Transportation, and the Susan G. Komen for the Cure Foundation. He has published more than 70 peer-reviewed articles in leading conferences and journals including SIGKDD, WSDM, ICDM, SDM, CIKM, TKDE, DMKD, TVCG, and PAMI. He received the Best Application Paper Award at the ACM SIGKDD conference in 2010; Best Poster Award at the IEEE VAST conference in 2014; and was a finalist of the INFORMS Franz Edelman Award Competition in 2011.

Reddy is a senior member of the IEEE and life member of the ACM.

Associate Professor
Research Areas:
  • iconHealth Informatics
Phone: 571-858-3307
Email

Projects

Computational Methods for Promoting and Predicting Project Campaigns in Crowdfunding Environments EAGER: An Integrated Predictive Modeling Framework for Crowdfunding Environments
Research Areas:
  • iconForecasting
Dates: August 15, 2016July 31, 2018
Sponsors:
  • National Science Foundation
Rehospitalization Analytics: Modeling and Reducing the Risks of Rehospitalization This project provides a comprehensive and accurate assessment of risk of rehospitalization and has the potential to direct more aggressive treatments towards specific high-risk patients.
Research Areas:
  • iconForecasting
  • iconHealth Informatics
Dates: August 15, 2016July 31, 2018
Sponsors:
  • National Science Foundation
Event Detection and Analysis in Longitudinal Data New Machine Learning Approaches for Modeling Time-to-Event Data
Research Areas:
  • iconForecasting
Dates: September 1, 2015August 31, 2018
Sponsors:
  • National Science Foundation

Sponsors

Chandan Reddy's Timeline

Year: 2007

Ph.D. in Computer Engineering, Cornell University

Year: 2010

Best Application Paper Award, ACM SIGKDD Conference

Year: 2011

Finalist in INFORMS Franz Edelman Competition

Year: 2012

Best Paper Nomination, SIAM International Conference on Data Mining

Year: 2014

Best Poster Award, IEEE Vast Conference