Mohammad Zhalechian

Assistant Professor of Operations and Decision Technologies
Kelley School of Business, Indiana University

Research Fellow, Center for the Business of Life Sciences
Faculty Affiliate, Institute of Business Analytics

Research Interests

Data-driven decision-making

Developing learning and optimization methods that use evolving data to improve decisions under uncertainty. I study how decision systems can adapt as new information arrives, learn from prior outcomes, and remain effective when conditions change.

Human-AI collaboration

Designing decision processes in which algorithms and experts complement one another. I study how algorithmic recommendations influence human judgment and how systems can support appropriate reliance, effective oversight, and better decisions than either humans or AI could produce alone.

Deployment and policy

Translating analytical methods into tools and policies that work in real organizations. I collaborate with practitioners to implement decision systems, evaluate how they affect behavior and outcomes, and identify what is required for responsible adoption at scale.

Much of my collaboration has been in healthcare and life sciences, though my work also extends to other domains — including revenue management and pricing, service operations, supply chain, and public policy.

Bio

I am an Assistant Professor of Operations and Decision Technologies at the Kelley School of Business, Indiana University, where I am a research fellow at the Center for the Business of Life Sciences and a faculty affiliate at the Institute of Business Analytics. I received my Ph.D. in Industrial and Operations Engineering from the University of Michigan, along with an M.A. in Statistics, and spent a year as a postdoctoral fellow at Harvard University.

My research sits at the intersection of machine learning, operations research, and public policy. I study how to design, deploy, and evaluate algorithmic systems that support human decision-makers when the stakes are high. I aim to pair methodological depth with implementation in environments where decisions carry real impact. I have worked with hospitals to put an online bed assignment tool into daily use at Michigan Medicine, with Medisoft in the United Kingdom to validate a glaucoma progression prediction tool across multiple centers, and on redesigning the FDA's medical device clearance pathway around human-algorithm collaboration. I study both the mathematical properties of these systems and the way people actually respond to them.

My work has been published in outlets including Management Science, Operations Research, and Manufacturing & Service Operations Management, as well as clinical journals such as the American Journal of Ophthalmology, and has been recognized in several best-paper competitions, including those of the INFORMS Minority Issues Forum (MIF), the INFORMS Decision Analysis Society (DAS), and the POMS College of Healthcare Operations Management (CHOM).