Ph.D. Candidate, Department of Industrial Engineering & Operations Research
Columbia University in the City of New York
3
Papers Released
3
Talks Given
4
Courses Taught
December 29, 2025
The Nonstationarity-Complexity Tradeoff in Return Prediction posted.
October 21, 2025
Present Data-Driven DFM via Manifold Learning paper at the October IAQF Thalesians Seminar Series.
September 19-21, 2025
Present Graph Machine Learning paper at the Northern Finance Association 2025 main conference.
July 15-18, 2025
Data-Driven DFM via Manifold Learning paper featured as a plenary talk by Agostino Capponi at the SIAM-FM25 conference.
June 24, 2025
Data-Driven Dynamic Factor Modeling via Manifold Learning posted.
June 9-12, 2025
Present Graph Machine Learning paper at the 17th Annual Society for Financial Econometrics Conference.
March-April, 2025
Graph ML paper accepted at SoFiE, NFA, inaugural FRR conferences.
December 9, 2024
Graph Machine Learning for Asset Pricing posted.
J. Antonio Sidaoui is a Ph.D candidate at Columbia University's Department of Industrial Engineering & Operations Research. He joined the department in 2023 after obtaining an M.S. in Statistics & Data Science at Yale University and a B.A. and B.S. in Mathematical Economics and Statistics at the University of Pennsylvania, Wharton School respectively.
J. Antonio's research focuses on the discovery and design of novel Machine Learning methodologies for financial applications, most recently Graph Machine Learning for Asset Pricing and Manifold Learning for Data-Driven Risk Management.
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