Shankar Prawesh

Prof. Shankar Prawesh works in the area of machine learning, recommender systems, 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 Management Sciences (DOMS) at IIT Kanpur. 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 leading manufacturing and airline booking firms. He has been cited as one of the most prolific researchers in news recommendation. 

Research Interest: AI/ML, Recommender Systems, Algorithm Design & Agent Based Modeling

Work Experience

     Associate Professor,  Department of Management Sciences, IIT, Kanpur               2022-Present

Assistant Professor, Department of Management Sciences, 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

Personalized Recommender System for Airline Industry 

 with Amadeus Software Labs, Bangalore (Nov 2023 - Nov 2024, role: PI) 

Experiments and modeling of pedestrian dynamics to create a designing tool for crowded public spaces

      with SERB (CRG), DST, India (May 2023-May 2026, role: PI)

Machine learning algorithms for large-scale job-shop scheduling       

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

      Status: granted patent in Japan in July 2024

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

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

JOURNAL PUBLICATIONS

Somnath Bhattacharya and Shankar Prawesh. Design and Evaluation of News Recommender System: A Variety Seeking Perspective. Asia Pacific Journal of Information Systems, 35(1), 146-176, 2025, https://doi.org/10.14329/apjis.2025.35.1.146

Shivam Kushwaha, Anand Venkatesh and Shankar Prawesh. A decentralized production approach to measure fuel performance of bus transportation systems. Managerial and Decision Economics, 45(6), 4157–4172, 2024, https://doi.org/10.1002/mde.4241

Somnath Bhattacharya and Shankar Prawesh. A review of challenges, algorithms and evaluation methods in news recommendation. Journal of Information Science, 0(0), 2024, https://doi.org/10.1177/01655515241244497

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 

PATENTS

Koga Yuichi, Watabe Yosuke, Shankar Prawesh, Avijit Khanra, and Faiz Hamid. 2024. Scheduling device, method and program. JP7508064B2, filed August 28, 2020, and issued July 1, 2024. https://patents.google.com/patent/JP7508064B2

PROFESSIONAL COURSES DEVELOPED

Big Data and Data Analytics

for mid-level executives at Maruti Suzuki India Ltd. (2024)

      Artificial Intelligence and Machine Learning

    for mid-level executives at Maruti Suzuki India Ltd. (2024)

Criminal Justice Data Analysis 

 for police officers (2020-21), jointly with:

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

SELECTED CONFERENCE PRESENTATIONS 

Kanika Jain, Indranil Saha Dalal and Shankar Prawesh, "A novel variable-goal approach as universal for pedestrian dynamics in any situation ", Pedestrian and Evacuation Dynamics (PED 2025) (accepted).

Pranjali Narayan, Avendra S Chandrawacar, Shankar Prawesh, "Personalized Airline Itinerary Recommendation using Choice Modelling ", India Conference on Information Systems (InCIS 2025). 

Shankar Prawesh, Avijit Khanra, Neha Kadu, Naoyuki Fujiwara, Yuichi Koga, Yosuke Watanabe, "Software Design for Real-time Large-scale Production Scheduling ", WITS 2023.

Akash Sonowal, Shankar Prawesh, "Interpolating Neural Networks for Econometric Modelling", India Finance Conference 2023. 

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-until now, 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.

COMPLETED PHD SUPERVISION

Consumer-Centric Design of Recommender Systems (Somnath Bhattacharya, Jain University Bangalore).

Analysis of operation efficiency using data envelopment analysis (DEA) in transportation (Shivam Kushwaha, IRMA Anand).

RECENT MASTER’S THESIS SUPERVISION

      Personalized Recommendation: A Survey and an Econometric Approach to Algorithm Design (Avendra S Chandrawacar, 2024)

      Interpolating Neural Networks for Econometric Modelling (Akash Sonowal, 2022)

      Aspect Based Helpfulness Prediction of Product Review Data (Motilal Meher, 2020)

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

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, DPGC 2021-22. 

AWARDS AND RECOGNITIONS

Cited as one of the top researcher in News Recommendation (2024), ACM TORS https://doi.org/10.1145/3654805

College of Business Outstanding Doctoral Student Research Award 2012

University of South Florida, Graduate Fellowship 2009 – 2010