Sudip Gupta, PhD

Professor of Practice

Academic Area	Finance
Academic Area	Economics

Dr. Sudip Gupta is a Professor of finance at Johns Hopkins Carey Business School. His current research and teaching interests are in the areas of Artificial Intelligence-Machine Learning, Auctions, ESG, Healthcare and Fintech. He is an award-winning teacher, and his research has appeared in top academic journals and received best paper awards. He has written papers in the areas of algorithmic bias, alternative credit rating using machine learning, credit derivatives, ESG ratings and portfolio formation with alternative data, generative AI, nowcasting with alternative data, treasury auctions 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 multiple 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, a fellow of the Centre for Responsible AI and consults various multinational financial corporations and government committees. He also served as a consulting expert for multiple antitrust and financial litigations.

Education

PhD, Economics, University of Wisconsin Madison
MS Economics, University of Wisconsin Madison

Research

Selected publications

Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech” (with Sumit Agarwal, Shashwat Alok and Pulak Ghosh) (2023) Journal of Money Credit and Banking
“Public vs. Private Information: Firm Disclosures, SEC Letters and the JOBS Act” (with Sumit Agarwal and Ryan Israelsen) Quarterly Journal of Finance, September (2022), 12-03, pp. 1-42, (Best Paper Award)
"Underwriting Government Debt Auctions” (with Rangarajan K Sundaram and Suresh M Sundaresan) Management Science, (2021) 675, pp. 2657-3320
“Strategic Overbidding for Toehold in Dynamic Auctions: Structural Estimation of the Synergy Effect”, Production and Operations Management, (2021), 30-2, pp. 584-605
“Mispricing and Arbitrage in CDS Auctions” (with Rangarajan K Sundaram) Journal of Derivatives, (2015), 22-4, pp. 79-91
“Inventory Effects, The Winner’s Curse and Bid Shading in CDS Auctions Outcomes” (with Rangarajan K Sundaram) Journal of Derivatives, (2015), 23-2, pp. 36-52
“Shareholder Litigation Rights and Firm Productivity” (with Alona Bilokha), Financial Markets, Institutions & Instruments, (2023)
“Emerging Firms’ Cost of Audit and Audit Quality” (with Joseph Micale, Ashok Rubin and Rong Yang) Accounting and Business Review, (2024)

Working Papers

“Algorithmic Bias and Health Equity”
“Alternative data based ESG ratings and portfolio”
“Nowcasting with Alternative data and machine learning”

Teaching

Current

Empirical Finance
Machine Learning for Finance
Linear Econometrics for Finance
Financial Institutions
Investments

Honors and Distinctions

Best Paper Published in Quarterly Journal of Finance in 2022
Nomination: Carey Faculty Service and Mentorship Award, 2023
Co-Principal Investigator: Nexus (Convening) Award for Artificial Intelligence for Health Equity Research (AIHE) at 555 Penn, Johns Hopkins University, 2023 ($100,000)
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 (multiple years)