Dr. Rahul Kumar is an Assistant Professor in the area of Information Systems at Indian Institute of Management (IIM) Sambalpur. Prior to this, he was at the Xavier Institute of Management Bhubaneswar (XIMB) in the Decision Science area. There, he was Joint Coordinator for the Executive MBA program in Business Analytics. He holds his doctorate (FPM) from Indian Institute of Management (IIM) Ranchi. Post PhD, he had a brief stint at Industry as an Analytics Consultant at Infosys Consulting. By background he is an engineer from BIT Mesra, Ranchi. Prior to joining IIM Ranchi as a doctoral scholar, he was working as a Manager at Jusco Pvt Ltd., A TATA STEEL Subsidiary.
Quantitative Techniques for Management
Machine Learning and Artificial Intelligence
1. R. Kumar and P. K. Bala. “Recommendation Engine based on derived wisdom for more similar item neighbors”, Information Systems and e-Business Management, Springer Publication, August 2017, Volume 15, Issue 3, pp 661–687. http://link.springer.com/article/10.1007/s10257-016-0322-y
2. S. Snehvrat, A. Kumar, R. Kumar and S. Dutta, “The State of Ambidexterity Research: A Data Mining Approach”, International Journal of Organizational Analysis @ Emerald Publishers (accepted for publication)
3. R. Kumar and P. K. Bala. “Identifying meaningful neighbors for an improved recommender system”, Journal of Modelling in Management. Emerald Publishing House (forthcoming: Vol: 12 Iss: 2).
4. A. Kumar, R. Kumar, S. Dutta, R. Kumar and A. Mukherjee. “Reconceptualizing co-opetition using text mining: inductive derivation of a consensual definition of the field (1996-2015)”. International Journal of Business Environment. Inderscience Publishers, Vol. 9, No. 2, 2017.
5. R. Kumar, P. K. Bala and Shubhadeep Mukherjee “Improving recommendation quality by identifying more similar neighbours in a collaborative filtering mechanism”, International Journal of Operational Research. Inderscience Publishers (Accepted for Publication).
6. R. Kumar, P. K. Bala and Shubhadeep Mukherjee , “A New Neighborhood Formation Approach for Solving Cold-Start User Problem in Collaborative Filtering”, International Journal of Applied Management Science, In Press, Inderscience.