Dr. Sudip Gupta is an associate professor of finance at Johns Hopkins Carey Business School. His current research and teaching interests are in the areas of Auctions, Big Data-Machine Learning, ESG and Fintech. He is an award-winning teacher, and his research has appeared in top journals. He has written papers in the areas of alternative credit rating using machine learning, credit derivatives, treasury auctions, nowcasting with alternative data, ESG ratings and portfolio formation with alternative data etc.
Prior to joining Carey, Prof Gupta was a faculty and director of the top ranked MSQF program of the Gabelli School of Business, Fordham University, where he had brought big data-machine learning in finance into the MS curriculum. Previously, Dr. Gupta was a full-time faculty and had taught at Indiana University’s Kelley School of Business, Indian School of Business (ISB), New York University’s Stern School of Business, and the University of Maryland’s Smith School of Business, in the areas of corporate finance, econometrics, fintech, investments, and machine learning at both undergraduate and graduate levels. He has received awards for both research and teaching. He has a PhD in economics from the University of Wisconsin, Madison.
Prof Gupta is a data hackathon champion and consults various multinational financial corporations and government committees. He also served as a consulting expert for multiple antitrust and financial litigations.
- PhD, Economics, University of Wisconsin Madison
- MS Economics, University of Wisconsin Madison
- "Underwriting Government Debt Auctions” (with Rangarajan K Sundaram and Suresh M Sundaresan) Management Science
- “Strategic Overbidding for Toehold in Dynamic Auctions: Structural Estimation of the Synergy Effect”, Production and Operations Management
- “Mispricing and Arbitrage in CDS Auctions” (with Rangarajan K Sundaram) Journal of Derivatives
- “Inventory Effects, The Winner’s Curse and Bid Shading in CDS Auctions Outcomes” (with Rangarajan K Sundaram) Journal of Derivatives
- “Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech”
- “Alternative data based ESG ratings and portfolio”
- “Nowcasting with Alternative data and machine learning”
- Linear Econometrics for Finance
- Computational Finance
Honors and distinctions
- Dean’s Award for Impact for excellence and high impact in research, teaching and service, GSB Data Hackathon Champion on Alternative data and nowcasting
- Trustee Teaching Award: Finalist, Kelley School of Business
- Best Paper Finalist, FMA
Impact and engagement
- Special Consultant: Economists Inc., 2009-
- Expert Advisor: Vega Economics, 2017-
- Advisor: Competition Commission of India
- Member: Big Data Task Force Group, State of Karnataka Knowledge Commission