Nachiketa Sahoo

Associate Professor, Information Systems

Nachiketa Sahoo is an associate professor in the Information Systems Department at the Questrom School of Business, Boston University. He does research at the intersection of Machine Learning and Information Systems. Typically, it focuses on learning user preferences and decision making processes from large disaggregate user-activity level datasets. He is particularly interested in developing methods for improved personalized recommendations. 

Selected Research Presentations

Benade, J. , Sahoo, N. Stability, Fairness and the Pursuit of Happiness in Recommender Systems, Workshop on Information Technologies and Systems (WITS), Copenhagen, Denmark, 2022

Publications

Song, Y., Sahoo, N., Srinivasan, S., Dellarocas, C. (In Press). “Uncovering Characteristic Response Paths of a Population”, Informs Journal on Computing

Padmanabhan, B., Fang, X., Sahoo, N., Burton-Jones, A. (2022). “Editor’s Comments: Machine Learning in Information Systems Research”, MIS Quarterly, 46 (5)

Song, Y., Li, Z., Sahoo, N. (2022). “Matching Returning Donors to Projects on Philanthropic Crowdfunding Platform”, Management Science

Akkas, A., Sahoo, N. (2020). “Reducing Product Expiration by Aligning Salesforce Incentives: A Data-driven Approach”, Production and Operations Management, 28 (8), 1992-2009

Song, Y., Sahoo, N., Ofek, E. (2019). “When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation”, Management Science, 65 (8), 3737-3757

Sahoo, N., Dellarocas, C., Srinivasan, S. (2018). “The Impact of Online Product Reviews on Product Returns”, Information Systems Research [10477047], 29 (3)

Singh, P., Sahoo, N., Mukhopadhyay, T. (2014). “How to Attract and Retain Readers in Enterprise Blogging?”, Information Systems Research, 25 (1), 35-52

Sahoo, N., Singh, P., Mukhopadhyay, T. (2012). “A Hidden Markov Model for Collaborative Filtering”, MIS Quarterly, 36 (4), 1329-1356

Sahoo, N., Krishnan, R., Duncan, G., Callan, J. (2012). “The Halo Effect in Multicomponent Ratings and Its Implications for Recommender Systems: The Case of Yahoo! Movies”, Information Systems Research, 23 (1), 231-246

Sahoo, N., Callan, J., Krishnan, R., Duncan, G., Padman, R. (2006). “Incremental hierarchical clustering of text documents”, Proceedings of the 15th ACM international conference on Information and knowledge management – CIKM ’06 357-357