V.G.Vinod Vydiswaran [Pronounciation Key: V. G. Vin-oh-d Vahy-deesh-wuh-ruhn]
	Assistant Professor of Learning Health Sciences Department of Learning Health Sciences University of Michigan Medical School 230 Victor Vaughan Building 1111 E. Catherine St Ann Arbor, MI 48109-2054. USA Email: vgvinodv [at] umich.edu (preferred) Phone: 734-763-0080 Research Interests Education and Affiliations Publications Teaching

Research Interests

My research interests are primarily in information trustworthiness, large-scale text mining and analysis, and natural language processing. I am also interested in data mining, information extraction, machine learning, building learning health systems, and working on interesting applications of algorithmic models to address real world challenges.

My current research focuses on mining and analyzing health information from multiple sources, including scientific literature, community health forums, and social and information networks. I am specifically interested in analyzing online medical textual information to infer credibility of sources and the claims they make.

Education

• (Aug 2007 - Dec 2012) Ph.D. in Computer Science, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
• (Jul 2002 - Jul 2004) M.Tech. from Indian Institute of Technology Bombay, Mumbai, Maharashtra, India.
• (Aug 1998 - Jun 2002) Bachelor of Engineering in Computer Engineering, Vishwakarma Institute of Technology, affiliated to the University of Pune, Pune, Maharashtra, India.
• (May 1986 - Jun 1998) Schooling from Kendriya Vidyalaya Ganeshkhind, Pune, Maharashtra, India.

Professional Experience

• (starting Jul 2015) Assistant Professor of Learning Health Sciences, Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, MI, USA
• (Aug 2013 - Jul 2015) Research Fellow and Research Investigator, School of Information, University of Michigan, Ann Arbor, MI, USA
• (Jan 2013 - Aug 2013) Postdoctoral Research Associate, Information Trust Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
• (May 2011 - Aug 2011) Research Assistant, Augmented Social Cognition Group, Palo Alto Research Center, Palo Alto, CA, USA. Visiting Researcher: Aug 2011 - Jun 2012
• (May 2010 - Aug 2010) Research Intern, Machine Learning Group, Microsoft Research, Redmond, WA, USA
• (Jul 2004 - Jul 2007) Research Engineer, Technology Research Group, Yahoo! Research & Development Center, Bangalore, India

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Teaching

• In Fall 2015, I will be teaching SI 671 - Data Mining: Methods and Applications. Please see the course website for additional details.

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Professional Service and Memberships

• Workshop co-organizer: TextGraphs-9, a workshop on Graph-based Methods for Natural Language Processing, held in conjunction with the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2014.
• Invited Reviewer:
  • ACM Transactions on Information Systems (TOIS), 2010-14
  • Information Processing Management (IPM), 2011-12
  • Journal of Natural Language Engineering (JNLE), 2014
• PC member:
  • AAAI Conference on Artificial Intelligence (AAAI), 2013
  • ACM Conference of Information and Knowledge Management (CIKM), 2013
  • American Medical Informatics Association Annual Symposium (AMIA), 2014
  • Conference on Empirical Methods in Natural Language Processing (EMNLP), 2013-14
  • Conference on Lexical and Computational Semantics (*SEM), 2013-14
  • European Conference on Information Retrieval (ECIR), 2014-15
  • International Joint Conference on Natural Language Processing (IJCNLP), 2013
• Association memberships:
  • American Society for Information Science and Technology (ASIS&T): 2011-13
  • Association for Computational Linguistics (ACL): 2008-10
  • Association for the Advancement of Artificial Intelligence (AAAI): 2008-09, 2013-14
  • Association of Computing Machinery (ACM): 2004-07

Special Mentions

• Certificate in Foundations of Teaching, awarded by the University of Illinois, 2012
• Outstanding Teaching Assistant award for Fall 2011, awarded by the Department of Computer Science, University of Illinois
• CS Graduate Ambassador, Department of Computer Science, University of Illinois (2010-11)
• Nominated to the first Graduate Academic Council (GAC), Department of Computer Science, University of Illinois (2009-10)

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Publications

Book Chapters and Tutorials

• Book chapter on Recognizing Textual Entailment            
  Mark Sammons, V.G.Vinod Vydiswaran, and Dan Roth.
  "Multilingual Natural Language Applications: From Theory to Practice.", Daniel M. Bikel and Imed Zitouni (Eds.), IBM Press, Pearson plc. May 2012.
  


• Tutorial on Information Trustworthiness    Link
  Jeffrey Pasternack, Dan Roth, and V.G.Vinod Vydiswaran.
  The 27th AAAI Conference on Artificial Intelligence (AAAI), 2013.
  


• Tutorial on Recognizing Textual Entailment            
  Mark Sammons, Idan Szpektor, and V.G.Vinod Vydiswaran.
  Human Language Technologies: The 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), 2010.
  

Journal articles

• Overcoming bias to learn about controversial topics.      
  V.G.Vinod Vydiswaran, ChengXiang Zhai, Dan Roth, and Peter Pirolli.
  Journal of the American Society for Information Science and Technology (JASIST), 2014. In press.
  

Conference and Workshop papers

• Mining consumer health vocabulary from community-generated text.            
  V.G.Vinod Vydiswaran, Qiaozhu Mei, David A. Hanauer, and Kai Zheng.
  In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), 2014. To appear
  


• User-created groups in health forums: What makes them special?            
  V.G.Vinod Vydiswaran, Yang Liu, Kai Zheng, David A. Hanauer, and Qiaozhu Mei.
  In Proceedings of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM), 2014.
  


• BiasTrust: Teaching biased users about controversial topics            
  V.G.Vinod Vydiswaran, ChengXiang Zhai, Dan Roth, and Peter Pirolli.
  The 21st ACM International Conference on Information and Knowledge Management (CIKM), 2012.
  


• Unbiased Learning of Controversial Topics            
  V.G.Vinod Vydiswaran, ChengXiang Zhai, Dan Roth, and Peter Pirolli.
  The 75th Annual Meeting of the American Society for Information Science and Technology (ASIST), 2012.
  


• Reliability Prediction of Webpages in the Medical Domain            
  Parikshit Sondhi, V.G.Vinod Vydiswaran, and ChengXiang Zhai.
  The 34th European Conference on Information Retrieval (ECIR), 2012.
  


• Content-driven Trust Propagation Framework                  
  V.G.Vinod Vydiswaran, ChengXiang Zhai, and Dan Roth.
  The 17th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2011.
  


• Gauging the Internet Doctor: Ranking Medical Claims based on Community Knowledge            
  V.G.Vinod Vydiswaran, ChengXiang Zhai, and Dan Roth.
  KDD Workshop on Data Mining for Medicine and HealthCare, 2011.
  


• News Sync: An Analysis of Scenario-based News Exploration            
  V.G.Vinod Vydiswaran, Jeroen van den Eijkhof, Raman Chandrasekar, Ann Paradiso, and Jim St. George.
  The 74th Annual Meeting of the American Society for Information Science and Technology (ASIST), 2011.
  


• Improving the Online News Experience            
  V.G.Vinod Vydiswaran and Raman Chandrasekar.
  The Fourth Workshop on Human-Computer Interaction and Information Retrieval (HCIR), 2010.
  


• News Sync: Three Reasons to Visualize News Better            
  V.G.Vinod Vydiswaran, Jeroen van den Eijkhof, Raman Chandrasekar, Ann Paradiso, and Jim St. George.
  The Fourth Workshop on Human-Computer Interaction and Information Retrieval (HCIR), 2010.
  


• "Ask not what Textual Entailment can do for You..."            
  Mark Sammons, V.G.Vinod Vydiswaran, and Dan Roth.
  The 48th Annual Meeting of the Association for Computational Linguistics (ACL), 2010.
  


• A Framework for Entailed Relation Recognition            
  Dan Roth, Mark Sammons, and V.G.Vinod Vydiswaran.
  The 47th Annual Meeting of the Association for Computational Linguistics (ACL), 2009.
  


• Finding Related Entities by Retrieving Relations: UIUC at TREC 2009 Entity Track            
  V.G.Vinod Vydiswaran, Kavita Ganesan, Yuanhua Lv, Jing He, and ChengXiang Zhai.
  Text Retrieval Conference (TREC), 2009.
  


• A Study of Term Proximity and Document Weighting Normalization in Pseudo Relevance Feedback -- UIUC at TREC 2009 Million Query Track            
  Yuanhua Lv, Jing He, V.G.Vinod Vydiswaran, Kavita Ganesan, and ChengXiang Zhai.
  Text Retrieval Conference (TREC), 2009.
  


• Relation Alignment for Textual Entailment Recognition            
  Mark Sammons, V.G.Vinod Vydiswaran, Tim Vieira, Nikhil Johri, Ming-Wei Chang, Dan Goldwasser, Vivek Srikumar, Gourab Kundu, Yuancheng Tu, Kevin Small, Joshua Rule, Quang Do, and Dan Roth.
  Text Analysis Conference (TAC), 2009.
  


• Opinion Summarization using Entity Features and Probabilistic Sentence Coherence Optimization: UIUC at TAC 2008 Opinion Summarization Pilot            
  Hyun Duk Kim, Dae Hoon Park, V.G.Vinod Vydiswaran, and ChengXiang Zhai.
  Text Analysis Conference (TAC), 2008.
  


• Learning to extract information from large websites using sequential models            
  V.G.Vinod Vydiswaran and Sunita Sarawagi.
  The Eleventh International Conference on Management of Data (COMAD), 2005.
  Best Paper Award.
  

Posters, Articles, and Invited Talks

• Robust, Light-weight Approaches to compute Lexical Similarity            
  Quang Do, Dan Roth, Mark Sammons, Yuancheng Tu, and V.G.Vinod Vydiswaran.
  Computer Science Research and Technical Reports, University of Illinois, 2009.
  


• New Search Paradigms to Facilitate Meaning-based Information Retrieval            
  Quang Xuan Do, V.G.Vinod Vydiswaran, and Dan Roth.
  Poster, selected at the Second Annual DHS University Network Summit, Washington D.C., 2008.
  


• Learning to extract information from large domain-specific websites using sequential models            
  Sunita Sarawagi and V.G.Vinod Vydiswaran.
  The special issue of ACM SIGKDD Explorations on Web content mining, Dec 2004, Volume 6, Issue 2.
  


• Resolving Citations in a Paper Repository            
  Sunita Sarawagi, Sumana Srinivasan, V.G.Vinod Vydiswaran, and Kapil Bhudhia.
  ACM SIGKDD Explorations, December 2003, Volume 5, Issue 2.
  Second Prize and Best Technique, Data Cleaning Task (Task 2), KDD Cup 2003.
  

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Last Updated: August 10th, 2015