Shankar Prawesh 

Research, and Teaching
IIT Kanpur

Shankar Prawesh primary research area is in the field of agent-based simulation, machine learning and social media. He received his PhD in Management Information Systems from the University of South Florida and Integrated Master’s degree (5 year program) in Mathematics and Scientific Computing from IIT Kanpur. Currently Shankar is an assistant professor in the department of Industrial and Management Engineering at IIT Kanpur. Prior to joining IIT Kanpur he was a postdoctoral research associate at the Robert H. Smith School of Business, University of Maryland, College Park. Shankar’s research has been published in the leading conferences of information systems and computer science including ACM RecSys, ICIS, and WITS. Recently his doctoral research has been published in Information Systems Research (http://dx.doi.org/10.1287/isre.2014.0529) – a premier journal in Management Information Systems. In his free time he enjoys reading non-fiction books and travelling.

Principal Investigator

Further information

Projects within the Big Data Project/ Supervised students within the Big Data Project/ Anticipated projects
Research interest in relevance of the project
Field of Expertise
Selected publications
Complete list of publications
Contact details

Projects within the Big Data Project/ Supervised students within the Big Data Project/ Anticipated projects

SPONSORED RESEARCH PROJECTS 

  • Mitsubishi Heavy Industries, Ltd. (May 2018 – ongoing) -> Mitsubishi Heavy Industries, Ltd. (May 2018 – June 2019)
  • Machine learning algorithms for large-scale job-shop scheduling
  • with Mitsubishi Heavy Industries, Ltd. (May 2018 – ongoing)
  • High-speed optimization algorithm for large-scale job-shop scheduling 
  • with Mitsubishi Heavy Industries, Ltd. (May 2016 – June 2017)

PH.D. STUDENT SUPERVISION 

  • Text Analysis in Finance
  • Evaluation of Fair News Recommendation Algorithms using A/B testing

Research interest in relevance of the project

  • Social media and text analysis
  • Computational modelling and simulation
  • Machine learning and statistical modelling
  • Financial data analysis

Field of Expertise

  • Machine Learning
  • Social Networks
  • Text Analysis, Simulation 

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. http://dx.doi.org/10.1287/isre.2014.0529
  • Shankar Prawesh and Balaji Padmanabhan, “Multi-Objective News Recommender Systems”, (WITS 2015 – a premier workshop in Information Systems), Dallas, December 2015. 
  • 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, “The Top-N News Recommender: Count Distortion and Manipulation Resistance”, Fifth ACM Conference on Recommender Systems (RecSys’ 2011), Chicago, October 2011.

Complete list of publications

JOURNAL PUBLICATIONS

  • Shankar Prawesh and Balaji Padmanabhan (2014). The “Most Popular News” Recommender: Count Amplification and Manipulation Resistance. Information Systems Research, 25(3), 569–589. http://dx.doi.org/10.1287/isre.2014.0529
  • Shankar Prawesh, Manish Agrawal, and Kaushal Chari (2016). Effects of Project Owner’s Title on the Financial Impacts of IT Systems Integration Outsourcing Projects, Information Systems Management, 33(3), 199-211. https://doi.org/10.1080/10580530.2016.1188536

HIGHLY REFEREED CONFERENCE PROCEEDINGS

  • Shankar Prawesh and Balaji Padmanabhan, “Multi-Objective News Recommender Systems”, (WITS 2015 – a premier workshop in Information Systems), Dallas, December 2015.
  • Shankar Prawesh and Balaji Padmanabhan, “News Recommender Systems with Feedback”, Thirty Third International Conference on Information Systems, (ICIS’ 2012 – the premier conference in Information Systems), 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 REFEREED 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.

Contact details

Address:

Department of Industrial and Management Engineering
Room no. 307, IIT Kanpur

Phone: +91 512 259 6182

Swaprava Nath
Prithwijit Guha
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