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Shankar Prawesh

Shankar Prawesh

PhD (University of South Florida, College of Business)

Associate Professor, Department of Management Sciences

Research Interest

Social Media, Agent Based Simulation, Fairness in Big Data.

Office

Department of Management Sciences,
IIT Kanpur ,
Kanpur 208016

Education

PhD University of South Florida, College of Business, 2009-2013Thesis Title: Applications of Agent Based Approaches in BusinessThesis Supervisor(s):Balaji Padmanabhan, Kaushal Chari

Indian Institute of Technology, Kanpur. M. Sc. (Integrated-5 year program) in Mathematics and Scientific Computing, 2004-2009

Selected Publications

Shankar Prawesh and Balaji Padmanabhan (2014). The "Most Popular News" Recommender: Count Amplification and Manipulation Resistance. Information Systems Research, 25(3), 569–589. doi:10.1287/isre.2014.0529
Shankar Prawesh, Manish Agrawal, and Kaushal Chari (2015). Effects of Project Owner’s Title on the Financial Impacts of IT Systems Integration Outsourcing Projects, Accepted at Information Systems Management

Awards & Fellowships

College of Business Outstanding Doctoral Student Research Award 2012
University of South Florida, Graduate Fellowship 2009 – 2010

Conference Presentations

"Big Network Analysis for Influence Identification through Sampling of Network Graphs", Statistical Challenges in ecommerce Research (SCECR' 2014), Tel Aviv, Israel, June 2014 (with W. Rand and M. Henricks).
"An Analysis of Conversations on Twitter", 2014 Winter Conference on Business Intelligence, Salt Lake City, Utah, March 2014 (with P. Wiriyathammabhum, W. Rand and L. Raschid).
"Network Analysis for Influence Identification through Sampling of Network Graphs", 2014 Winter Conference on Business Intelligence, Salt Lake City, Utah, March 2014 (with W. Rand).
"Analysis of Probabilistic News Recommender Systems", 2012 Winter Conference on Business Intelligence, Salt Lake City, Utah, March 2012 (with B. Padmanabhan).
"Manipulation Resistant News Recommender Systems", 2011 Winter Conference on Business Intelligence, Salt Lake City, Utah, March 2011 (with B. Padmanabhan).

Professional Experience

Research Associate, Center for Complexity in Business Robert H. Smith School of Business, University of Maryland, College Park, 2013-2014

Ongoing Project

Simulation based Crowd Management for Disaster Prevention (with Indanil S. Dalal, Anurag Tripathi)
Feedback Based News Recommender Systems (with Balaji Padmanabhan, under review)
Text mining Approach to Measure Customer Satisfaction (with Amit Trivedi)

Invited Talks

  • "Social Media Analytics", (August 2015, Intel High Performance Computing Workshop, IIT Kanpur)
  • "Topological Data Analysis", (March 2015, Mathematical Sciences Initiative, IIT Kanpur)
  • "Feedback Models in Top-N News Recommender Systems", INFORMS 2012, session- Recommender Systems, Phoenix, Arizona, October 2012, (with B. Padmanabhan).
  • "Manipulation Resistant New Recommender Systems with Feedback", INFORMS 2012, session- Personalized Recommender Systems, Phoenix, Arizona, October 2012, (with B. Padmanabhan).
  • Santa Clara, California, June 2012 (Organized by IIT Kanpur Foundation).
  • "Manipulation in Top-N News Recommender Systems", INFORMS 2011, session- Artificial Intelligence, Charlotte, North Carolina, November 2011 (with B. Padmanabhan).
  • "Count Amplification in Top-N News Recommender Systems", INFORMS 2011, session- Information Systems, Charlotte, North Carolina, November 2011 (with B. Padmanabhan).

Highly Referred Conference Proceedings

  • Shankar Prawesh and Balaji Padmanabhan, "Multi-Objective News Recommender Systems", (WITS 2015, Dallas, TX, USA)
  • Shankar Prawesh and Balaji Padmanabhan, "News Recommender Systems with Feedback", Thirty Third International Conference on Information Systems, (ICIS' 2012), Orlando, December 2012
  • Shankar Prawesh and Balaji Padmanabhan, "Manipulation Resistance in Feedback Models of Top-N Recommenders", The 22nd workshop on Information Technologies and Systems, (WITS' 2012), Orlando, December 2012 (Best paper award, runner-up)
  • Shankar Prawesh and Balaji Padmanabhan, "Probabilistic News Recommender Systems with Feedback", Sixth ACM Conference on Recommender Systems, (RecSys' 2012 - the premier conference in Recommender Systems), Dublin, Ireland, September 2012
  • Shankar Prawesh and Balaji Padmanabhan, "Manipulation in Top-N News Recommender Systems", The 21st workshop on Information Technologies and Systems, (WITS' 2011), Shanghai, China, December 2011
  • Shankar Prawesh and Balaji Padmanabhan, "The Top-N News Recommender: Count Distortion and Manipulation Resistance", Fifth ACM Conference on Recommender Systems (RecSys' 2011), Chicago, October 2011

Other Referred Conference Proceedings

Shankar Prawesh and Balaji Padmanabhan, "Analysis of Probabilistic News Recommender Systems", Eighteenth Americas Conference on Information Systems (AMCIS' 2012), Seattle, Washington, August 2012.