Sriram Somanchi is an Assistant Professor of Business Analytics at Mendoza College of Business. His research harnesses the power of large-scale data and machine learning to discover subgroups that are statistically robust and theoretically grounded. Subgroup discovery is crucial to address contemporary business and management challenges, as we navigate away from generic ‘average’ solutions towards an era marked by increasingly customized solutions. His primary domain of application is in healthcare, where his methods contribute to the promise of personalization, improve the efficiency of healthcare delivery, and enrich the clinical and operational aspects of healthcare management. Additionally, he showcases the wide applicability of subgroup discovery methods to address important issues in digital experimentation, crowdsourcing, behavioral economics, and service operations. To solve these intricate problems, his research draws on a rich foundation in social science and statistical machine learning to develop and deploy methods that bridge these related, but distinct disciplines, thus breaking new ground in a nascent academic landscape.
His research has been published in the Journal of Machine Learning Research (JMLR), the Journal of Computational and Graphical Statistics (JCGS), ACM Transactions of Information Systems (ACM TOIS), Manufacturing and Service Operations Management (M&SOM), Production and Operations Management (POM), Journal of American Medical Association (JAMA) Network Open, Statistics and Medicine, as well as leading conferences.
Somanchi has a Ph.D. in Information Systems and Management from Heinz College at Carnegie Mellon University. He is a graduate of the Machine Learning Department at CMU and earned an M.E. in computer science from the Indian Institute of Science, Bangalore, India.