Sriram Somanchi is an Assistant Professor of Business Analytics at Mendoza College of Business. His research focuses on bridging the gap between machine learning and social science problems. His interests include developing computationally efficient statistical machine learning algorithms for pattern detection in massive, complex data and demonstrating the practical utility of applying these approaches to real-world problems. He has worked in the area of event and pattern detection in the domains of healthcare, digital experimentation, economic development, crowdsourcing, and social media. Somanchi also is interested in leading the development of machine learning and data-mining methods to enable data-driven decision making in organizations and public policy agencies. His research has been published in Journal of Machine Learning Research (JMLR), 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 Americal 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.