Clemente Romano
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Hi! I’m Clemente Romano, a third-year PhD student in mathematics at NYU’s Courant Institute. My advisor is Prof. Petter Kolm.
I am interested in applications of signature features to machine learning and quantitative finance, as well as optimal control and volatility forecasting. My current projects focus on stochastic filtering and optimal trade execution.
Background
I earned my BSc in mathematics at the University of Naples Federico II and my MSc in mathematics at the University of Trieste through its joint educational program with SISSA. I graduated with the highest honors, 110/110 cum laude, in both degrees. My bachelor’s thesis on Sobolev spaces was supervised by Prof. Nicola Fusco; my master’s thesis on the Kakeya conjecture was supervised by Prof. Guido De Philippis.
I came to NYU with interests in harmonic analysis and geometric measure theory, and gradually shifted my focus toward mathematical finance. Alongside my research, I have taken courses in NYU’s Mathematics in Finance program and served as a TA and grader for courses in the program.
Honors and Fellowships
- Jeffrey and Denise Rosenbluth Fellowship — NYU Courant, 2025 and 2026.
- SISSA Fellowship — Competitive fellowship supporting my MSc studies in the SISSA–University of Trieste joint educational program.
- Collegio Universitario Luciano Fonda — Fellow during my master’s studies.
Selected work
Signature-based optimal execution
A Python framework using path signatures and symbolic shuffle algebra to construct and solve quadratic optimal-execution objectives.
Kalman filtering with signatures
A numerical reproduction exploring how linear signature regression can recover the continuous-time Kalman-Bucy filter.
Prediction-market arbitrage research
ATP tennis data collection and cross-exchange arbitrage research using Polymarket and Kalshi.
Explore
Read about my projects, browse my code on GitHub, or connect on LinkedIn.