Associate Professor of Tech, Ops, & Stats, Leonard N. Stern School of Business, New York University
Machine Learning
Business Analytics
Choice Modeling
Assortment and Pricing Analytics
Revenue Management


June 11, 2020

New JAMA Viewpoint article on the importance of LTC populations in Covid-19 modeling

I am pleased to announce the publishing of an important JAMA Viewpoint article I contributed to, along with my long-term collaborator Prof. Lakshminarayanan Subramanian. The article […]
June 10, 2020

Prof. Jagabathula presents at the virtual “AI & ML Colloquium” at Kelley Business School, Indiana University

On June 10, 2020, I gave a talk at the virtual “AI and Machine Learning Colloquium” organized by the Department of Operations and Decision Technologies at […]
May 21, 2020

Dr. Dmitry Mitrofanov successfully defends his dissertation!

Congratulations to Dr. Dmitry Mitrofanov for successfully defending his excellent PhD dissertation: “Choice-based demand models for emerging applications in retail and online platform operations.”  


  • Jan 2018-presentNew York University Stern School of Business, New York, NY

    Associate Professor of Information, Operations, and Management Sciences - Jan 2018–present
  • Jul 2018–Jun 2019Harvard Business School, Cambridge, MA

    Visiting Associate Professor of Technology and Operations Management
  • Oct 2011-Dec 2017New York University Stern School of Business, New York, NY

    Assistant Professor of Information, Operations, and Management Sciences
  • 2014–2019Celect, LLC, Retail Analytics Start-up, Boston, MA

    Co-founder of a big data retail analytics start-up that is commercializing my research on choice modeling. Raised capital (Seed, Series A) from top-tier VCs and Federal sources and helped build the initial team. Implemented the technology platform at multiple top-tier US retailers. The startup has now been acquired by Nike.


Srikanth Jagabathula is Associate Professor of Technology, Operations, and Statistics at the Leonard N. Stern School of Business, New York University. He is also affiliated with the NYU Center for Data Science. He received the PhD degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and held the Visiting Associate Professor position in the Technology and Operations Management Unit at the Harvard Business School in 2017-18.

His research lies at the intersection of machine learning and operations management. His work has focused on estimating large-scale demand models from choice data (e.g., sales transactions data) and then making operational decisions, such as assortment and price decisions (what to offer and what prices to charge). His methods have been applied in crowdsourcing, e-commerce, brick-and-mortar retail, and online platform settings. More recently, he has been interested in applying ideas from reinforcement learning and interpretable ML techniques to improve business decision-making.

Srikanth has received six "Best Paper" awards and nominations, a CAREER award from the National Science Foundation, the POMS Wickham-Skinner Early Career Researcher Award, and the IIT Bombay President of India Gold Medal. He was also recognized by Poets & Quants as one of the “40 Best Business Professors Under 40.”


Wickham Skinner Early-Career Research Accomplishments Award

2018, awarded by the POM society to academics with unusually high accomplishment ealy in their careers

Poets & Quants 40 Best Business Professors Under 40

2018, awarded each year to the 40 most impactful young business professors in both research and teaching

Best OM Paper in Management Science Award

2016, awarded to the best paper in the OM department from the last three years (2013-2015)