Shankar Prawesh

Prof. Shankar Prawesh works in the area of machine learning, digital marketing, and algorithm design. He earned his integrated master’s degree (5 years) in Mathematics and Scientific Computing from IIT Kanpur and his Ph.D. in Management Information Systems from the University of South Florida. After a brief stint as a postdoctoral research associate at the University of Maryland, College Park, Shankar joined the department of Industrial and Management Engineering at IIT Kanpur as an assistant professor. His research work has appeared in leading management and computer science outlets, including Information Systems Research and ACM RecSys. He has worked on research projects at Mitsubishi Heavy Industries and a few e-commerce startups.

Research Interest: Machine Learning, Social Media, Digital Marketing

Work Experience

Associate Professor, Industrial and Management Engineering (IME) IIT, Kanpur 2022-Present

Assistant Professor, Industrial and Management Engineering (IME) IIT, Kanpur 2014-2022

Research Associate, Center for Complexity in Business

Robert H. Smith School of Business, University of Maryland, College Park 2013-2014

EDUCATION

University of South Florida, Muma College of Business 2009-2013

Dissertation Title: Agent Based Modeling in Business

Ph.D. in Management Information Systems

Indian Institute of Technology, Kanpur

M. Sc. (Integrated-5 year program) in Mathematics and Scientific Computing 2004-2009

SPONSORED RESEARCH PROJECTS

Machine learning algorithms for large-scale job-shop scheduling

with Mitsubishi Heavy Industries (MHI), Ltd. (May 2018 – June 2019, role: PI).

High-speed optimization algorithm for large-scale job-shop scheduling

with MHI, Ltd. (May 2016 – June 2017, role: co-PI).

Status: jointly (with MHI) applied for patent in Japan in August 2020

JOURNAL PUBLICATIONS

Shivam Kushwaha, Shankar Prawesh, and Aanand Venkatesh. Does capacity utilization influence financial performance? A study of Indian public bus transport companies. Benchmarking, 2021, ISSN 1463-5771, https://doi.org/10.1108/BIJ-01-2021-0039

Shankar Prawesh and Balaji Padmanabhan. A Complex Systems Perspective of News Recommenders: Guiding Emergent Outcomes with Feedback Models. PLoS ONE, 16(1), 2021 https://doi.org/10.1371/journal.pone.0245096

Shankar Prawesh, Kaushal Chari, and Manish Agrawal. Industry Norms as Predictors of IT Outsourcing Behaviors, International Journal of Information Management, 56, 2021,102242, ISSN 0268-4012, https://doi.org/10.1016/j.ijinfomgt.2020.102242

Shankar Prawesh, Manish Agrawal, and Kaushal Chari. Effects of Project Owner’s Title on the Financial Impacts of IT Systems Integration Outsourcing Projects, Information Systems Management, 2016, 33(3), 199-211. https://doi.org/10.1080/10580530.2016.1188536

Shankar Prawesh and Balaji Padmanabhan. The “Most Popular News” Recommender: Count Amplification and Manipulation Resistance. Information Systems Research, 2014, 25(3), 569–589. http://dx.doi.org/10.1287/isre.2014.0529

MANUSCRIPTS UNDER REVIEW

Big Network Analysis for Influence Identification on Social Networks (with Bill Rand) – revision submitted

MANUSCRIPTS UNDER PREPARATION

Design and Evaluation of News Recommenders: A Variety Seeking Perspective (with Somnath Bhattacharya).

COURSES DEVELOPED

Social Media Analytics (an MBA course at IIT Kanpur)

Criminal Justice Data Analysis – a professional development course for security personnel - jointly with:

Dr. Arvind Verma (Indiana University), Dr. Nisheeth Srivastava (IIT Kanpur), Dr. Suresh Lodha (University of California, Santa Cruz)

HIGHLY REFEREED CONFERENCE PROCEEDINGS

Shankar Prawesh and Balaji Padmanabhan, “Multi-Objective News Recommender Systems”, WITS 2015 (workshop on Information Technologies and Systems), Dallas, December 2015.

Shankar Prawesh and Balaji Padmanabhan, “News Recommender Systems with Feedback”, ICIS 2012 (International Conference on Information Systems), Orlando, December 2012.

Shankar Prawesh and Balaji Padmanabhan, “Manipulation Resistance in Feedback Models of Top-N Recommenders”, WITS 2012, Orlando, December 2012. (Best paper award, runner-up)

Shankar Prawesh and Balaji Padmanabhan, “Probabilistic News Recommender Systems with Feedback”, RecSys 2012 (ACM Conference on Recommender Systems), Dublin, Ireland, September 2012.

Shankar Prawesh and Balaji Padmanabhan, “Manipulation in Top-N News Recommender Systems”, WITS 2011, Shanghai, China, December 2011.

Shankar Prawesh and Balaji Padmanabhan, “The Top-N News Recommender: Count Distortion and Manipulation Resistance”, RecSys 2011, ACM Conference on Recommender Systems, Chicago, October 2011.

INVITED TALKS AND PANEL DISCUSSIONS

"Machine Learning for Large-scale Production Scheduling", Reva University, Bengaluru (July 2021)

“Data Science with Industrial Perspectives”, Defence Institute of Advanced Technology (DIAT), Pune (April 2021)

“Social Media – A Modern Day Dilemma”, PRAGYAN, NIT Trichy (April 2021)

“Dynamics of Complex Systems (DCS 2019)”, ICTS-TIFR Bengaluru (May 2019)

“Modeling Online News as Complex Adaptive Systems”, (August 2018, Department of Management Studies, IIT Delhi)

“Social Media Analytics”, (August 2015, Intel High-Performance Computing Workshop, 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).

REFEREE ACTIVITIES

Journals: MIS Quarterly, INFORMS Journal on Computing, IIMB Management Review, IEEE Transactions on Engineering Management.

Conferences: ICDM (IEEE International Conference on Data Mining) 2014, WITS 2014-2015, ICIS 2012-2018, Associate editor ICIS 2020.

CONFERENCE COMMITTEE

EAD organized by MDI Gurgaon (Conference on Enterprise Architecture in the Digital Era) 2019.

DESRIST organized by IIT Madras (Design Science Research in Information Systems and Technology) 2018.

DIGITS organized by Robert H. Smith School of Business and BIMTECH (Digital Innovations, Transformation, and Society Conference) 2018.

ONGOING PHD SUPERVISION

Consumer-Centric Design of Recommender Systems (Somnath Bhattacharya, status: completed state of the art seminar) - nominated for Best Dissertation Proposal Award at WITS 2020

Machine Learning Methods for Portfolio Selection (Amit Trivedi, status: completed state of the art seminar)

Large Scale Job Shop Scheduling Problem (Neha Kadu, status: completed state of the art seminar)

Analysis of operation efficiency using data envelopment analysis (DEA) in transportation (Shivam Kushwaha, status: completed state of the art seminar) - selected for presentation at COSMAR19 organized by IISc Bangalore

RECENT MASTER’S THESIS SUPERVISION

Aspect Based Helpfulness Prediction of Product Review Data (Motilal Meher, 2020) - received Mr. & Mrs. S.N. Mittal Gold medal

Portfolio Optimization with Performance-Based Regularization: Evidence from an Emerging Market (Dhruv Patel, 2020) - received Shailja Srivastava Award

Job Shop Scheduling using Reinforcement Learning (Ankush Ojha, 2019)

Dynamic Portfolio Management using Multi-armed Bandit (Abhishek Mishra, 2019)

Bayesian Approach for Selected Problems from Business Analytics (Durga Kant Gupta, 2018)

Job Shop Scheduling using Artificial Neural Network (Subh Lakshmi Baranwal, 2017)

Application of machine learning in job shop scheduling (Rusheel Shukla, 2017)

ADMINISTRATIVE RESPONSIBILITIES

Warden, Hall-12 (2016-2019)

MTech. admission coordinator 2015-16, Ph.D. admission coordinator 2017

AWARDS AND HONOURS

College of Business Outstanding Doctoral Student Research Award 2012

University of South Florida, Graduate Fellowship 2009 – 2010