BIO

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.”

ACADEMIC APPOINTMENTS

  • 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

EDITORIAL APPOINTMENTS

  • 2019Associate Editor.

    Management Science Special Issue on Data-Driven Prescriptive Analytics
  • 2018Associate Editor.

    Management Science
  • 2018Associate Editor.

    Operations Research

PROFESSIONAL EXPERIENCE

  • 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.
  • Summer 2010A9.com (wholly-owned subsidiary of Amazon.com), Palo Alto, CA

    Designed and implemented a large-scale system to estimate the cannibalization effect of 3rd party ads on Amazon.com product pages
  • Summer 2009Microsoft Research, Silicon Valley, CA

    Analyzed large volumes of search queries to Bing. Designed and implemented a large-scale algorithm to recommend commercial queries to general search queries to increase traffic to Bing Shopping
  • Summer 2007Deutsche Bank AG, London, UK

    Designed and tested various quantitative models to value Collateralized Debt Obligations (CDOs)

EDUCATION

  • Jul 2008–Aug 2011Massachusetts Institute of Technology, Cambridge, MA

    PhD in Electrical Engineering and Computer Science, GPA 5/5
    Dissertation: “Nonparametric Choice Modeling: Applications to Operations Management”
    Advisors: Vivek Farias and Devavrat Shah
  • Sep 2006–Jun 2008Massachusetts Institute of Technology, Cambridge, MA

    S.M. in Electrical Engineering and Computer Science, GPA 5/5
    Dissertation: “Scheduling Algorithms for Arbitrary Communication Networks”
    Advisor: Devavrat Shah
  • Jul 2002–May 2006Indian Institute of Technology Bombay, Mumbai, India

    B. Tech. in Electrical Engineering, GPA 9.89/10
    Ranked first in the entire graduating class of 2006