Mendoza School of Business

Sriram Somanchi

Assistant Professor
IT, Analytics, and Operations
  344 Mendoza College of Business
  • Biography
  • Background
  • Publications

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), Management Information Systems Quarterly (MISQ), 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 (CMU). 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, Bengaluru, India.

Ph D, Carnegie Mellon University
MS, Carnegie Mellon University
M.Phil, Carnegie Mellon University
Master of Engineering, Indian Institute of Science
Bachelor of Technology, Jawaharlal Nehru Technological University

Areas of Expertise
Machine Learning
Business Analytics

"Business Analytics in Healthcare: Past, Current, and Future Trends", (With Kaitlin Wowak, John Lalor, Corey Angst), Manufacturing and Service Operations Management, 25, 2023

"Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-Observable Estimators", (With Benjamin Jakubowski, Edward McFowland III, Daniel Neill), Journal of Machine Learning Research, 24, 2023

"Examining User Heterogeneity in Digital Experiments", (With Ahmed Abbasi, Ken Kelley, David Dobolyi, Ted Yuan), ACM Transactions on Information Systems, 41, 2023

"Racial and gender inequities in the utilization of and outcomes after left ventricular assist devices among Medicare patients: A retrospective cohort study.", (With Thomas Cascino, Jeffrey McCullough), Journal of American Medical Association (JAMA) Network Open, 5, 2022

"To Predict or Not to Predict: The Case of Inpatient Admissions from the Emergency Department", (With Idris Adjerid, Ralph Gross), Production and Operations Management Journal, 32, 2022

"Discovering Anomalous Patterns In Large Digital Pathology Images", (With Daniel Neill, Anil Parwani), Statistics in Medicine, 2018