ICAIF 2025 - Workshop

AI Meets Quantitative Finance

Stochastic Methods as a Two-Way Bridge
Organized by Patrick C. S. PUN (NTU, Singapore) • Phillip S. C. YAM (CUHK, Hong Kong)

Artificial Intelligence (AI) has transformed financial modeling from deep learning for pricing & forecasting, to reinforcement learning (RL) for trading & execution. Yet the theoretical underpinnings remain underdeveloped for high-stakes finance. Quantitative Finance offers a rich toolkit, e.g., stochastic controls, mean-field games (MFGs), risk-sensitive optimization, that is interpretable and rigorous. These tools align closely with modern AI through perspectives like RL as control, MFG as multi-agent learning, and risk-aware learning via utility/risk functionals. This AI × Quant workshop focuses on the synergistic relationship between AI and Quantitative Finance, emphasizing stochastic methods as both tools and objects of analysis. To this end, we explore a two-way dialogue:

(i) how can advances in AI or machine learning push the frontier of financial modeling and decision-making? and
(ii) how can tools from stochastic analysis offer principled insights into the behavior (interpretability) and improvement (design/robustness) of AI methods?
Schedule
2:00–2:05 PM
Welcome Welcome Speech
2:05–2:45 PM
Keynote “Machine Learning and Control Theory” — Alain Bensoussan (UT Dallas)
2:45–3:10 PM
Plenary “An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control” — Mathieu Laurière (NYU Shanghai)
3:10–3:30 PM
Selected Lightning Talks (Accepted Papers) — A. A. Alzahrani (PIF), A. Chinta (JPMC), O. Pricilia (Oxford)
3:30–4:00 PM
Poster Coffee Break and Poster Presentation
4:00–4:40 PM
Keynote “Deep Filtering” — George Yin (UConn)
4:40–5:05 PM
Plenary “DeepMartingale: Duality of the Optimal Stopping Problem with Expressivity” — Hoi Ying Wong (CUHK)
5:05–5:30 PM
Plenary “The Exploration-Exploitation-Robustness Tradeoff in an Optimal Stopping Problem with Learning” — Andrew Lim (NUS)
5:30 PM
Closing Closing Remarks
Keynote/Plenary Speakers
Alain Bensoussan
Keynote Speaker
Alain Bensoussan

Lars Magnus Ericsson Chair, Professor of Management; IEEE Fellow, SIAM Fellow, AMS Fellow

University of Texas at Dallas

Wikipedia Profile Web
George Yin
Keynote Speaker
George Gang Yin

Professor of Mathematics; IEEE Fellow, IFAC Fellow, SIAM Fellow, AMS Fellow

University of Connecticut

Website
Andrew Lim
Plenary Speaker
Andrew Ee Beng Lim

Professor of Analytics and Operations

National University of Singapore

Website
Hoi Ying Wong
Plenary Speaker
Hoi Ying Wong

Professor of Statistics and Data Science

The Chinese University of Hong Kong

Website
Mathieu Laurière
Plenary Speaker
Mathieu Laurière

Assistant Professor of Mathematics and Data Science

NYU Shanghai

Website
Poster Presentation (Accepted Papers)

The following papers are accepted for poster presentation in this workshop:

  • A. A. Alzahrani (PIF): Deep Signature and Neural RDE Methods for Path-Dependent Portfolio Optimization Lightning Talk
  • A. Chinta (JPMC), L. Vinh Tran, and J. Katukuri: A Generalized Prob. Foundation Model with Deep Evidential Reg. for Portfolio Optimization Lightning Talk
  • O. Pricilia (Oxford) and M. Monoyios: Neural Functionally Generated Portfolios Lightning Talk
  • S. Molavipour (SEB Group), A. M. Javid, C. Ye, B. Löfdahl, and M. Nechaev: Robust Yield Curve Estimation for Mortgage Bonds Using Neural Networks
  • G. Verbii, M. Sokolovskii, G. Kilinkarov, D. Goryunov, and V. Yafarov (MIPT): Self-Organizing Maps for Spatiotemporal Analysis of SSVI Vol. Surface Regimes
  • A. G. Srinivasan, A. J. Said, S. Pentela (IIT Madras), V. Dwivedi, and B. Srinivasan: Towards Fast Option Pricing PDE Solvers Powered by PIELM
  • R. Slepaczuk (UWarsaw) and F. Stefaniuk: A Neural Network Informer In Algorithmic Investment Strategies on High Frequency Bitcoin Data
  • P. Sakowski (UWarsaw) and J. Maskiewicz: Can AI Trade Fin. Mkts? Auton. Fin. Trading with DRL: Comparative Study of DDQN, PPO, & Network Archt.
  • G. Verbii, G. Kilinkarov (MIPT), M. Sokolovskii, D. Goryunov, and V. Yafarov: Opt. Stopping via Martingale Rainbow Deep Q-Learning: Risk-Sensitive Fin. DM
    • Organizers
    Patrick Chi Seng Pun
    Organizer
    Patrick Chi Seng Pun

    Associate Professor of Mathathematical Sciences

    Nanyang Technological University

    Website
    Phillip Sheung Chi Yam
    Organizer
    Phillip Sheung Chi Yam

    Professor of Statistics and Data Science

    The Chinese University of Hong Kong

    Website
    Organized by Members of the Following Institutions
    Archived Paper Submission Details

    We invited high-quality research contributions to this workshop. Submissions were handled via EasyChair and were reviewed in a single-blind manner. Accepted papers were invited for poster presentation. We further invited the author(s) of some selected paper(s) to give a lightning talk in this workshop.

    Contact organizers: Patrick at cspun@ntu.edu.sg (Primary) • Phillip at scpyam@cuhk.edu.hk  |  © ICAIF 2025 Workshop "AI Meets Quantitative Finance"