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NeurIPS 2025 Workshop
🗓️ December 6th 2025 (Saturday)
📍 San Diego Convention Center
This workshop aims to foster cross-disciplinary collaboration at the intersection of generative AI and finance, a high-stakes domain where the integration of domain expertise is essential to the safe and effective deployment of machine learning technologies. Recent advances in generative models—ranging from large language models to diffusion and score-based generative architectures—have opened new frontiers for applications in finance, such as financial modeling, stress testing, scenario generation, automated financial services, and decision-making under uncertainty. The workshop will highlight theoretical advances, practical implementations, new opportunities, and open challenges that arise when adapting generative AI to financial systems under unique constraints, such as data sparsity, regulatory requirements, and highly non-stationary and adversarial environments. By bringing together the computer science community, financial researchers, industry practitioners, and regulators, we aim to catalyze interdisciplinary dialogue and accelerate the responsible development of generative AI tailored to the needs of finance and risk management.
We are grateful for the supports from Cubist Systematic Strategies, Domyn, and RBC Borealis to the workshop!
Speakers
Speakers
Rama Cont (Oxford, math finance and ML in finance). Rama Cont is Professor of Mathematics and Chair of Mathematical Finance at the University of Oxford. Rama Cont’s research focuses on stochastic analysis, stochastic processes, machine learning in finance, and mathematical modeling in finance, in particular the modeling of extreme market risks, liquidity risk and systemic risk.
Furong Huang (UMD, generative AI and trustworthy ML). Furong Huang is an Associate Professor of Computer Science at the University of Maryland, specializing in trustworthy machine learning, sequential decision-making, and high-dimensional statistics. Her research focuses on developing reliable, interpretable models and practical algorithms that balance performance with ethical and safety considerations.
Bayan Bruss (Capital One, AI for financial services). Bayan Bruss is the VP of AI Foundations at Capital One and in this role he works with academic researchers to translate the latest research to address fundamental problems in financial services.
Ioana Boier (NVIDIA, Global Head of Capital Markets Strategy).
Jacob Chanyeol Choi (LinqAlpha, GenAI for hedge funds). Dr. Jacob Chanyeol Choi is the Co-Founder and CEO of LinqAlpha, a GenAI-native market intelligence and analytics platform for institutional investors. He holds a PhD in Electrical Engineering and Computer Science (EECS) from MIT. His research focuses on natural language processing (NLP) and the development of retrieval-augmented generation (RAG) systems for fundamental research in global markets.
Alejandro Lopez-Lira (University of Florida, GenAI in finance). Alejandro Lopez-Lira is an Assistant Professor of Finance at the University of Florida’s Warrington College of Business. His research focuses on asset pricing, machine learning, and textual analysis, exploring the intersection of AI and finance.
Tal Kachman (Radboud University (Netherlands), reinforcement learning and AI agents). Tal Kachman is an assistant professor in the department of artificial intelligence at Radboud university in the Netherlands leading the complex learning group. He is a member of the donders institute of brain cognition and behavior. Tal’s focus is on the crossroad between complex systems, the natural sciences and AI where his main focus is on how can AI systems help us understand and solve problems in markets, and translating solutions and insights to fundamental improvements of AI.
Hao Ni (UCL, generative AI and representation learning for Finance). Hao Ni is Professor of Mathematics at University College London (UCL) and a Turing Fellow at the Alan Turing Institute. Her research interests include stochastic analysis, financial mathematics, and machine learning. She is interested in the non-parametric modelling effects of complex multi-modal data streams through rough paths theory and machine learning. Moreover, she has research interests on real-world applications, such as human-computer interface, computer vision, and finance.
Panel
Panel
Prakash Arunachalam (AI Hub at Bank of New York Mellon, Director of Data Science). Dr. Prakash Arunachalam is leading a team of data scientists at AI Hub in BNY Mellon. He is responsible for Machine Learning Models and Responsible AI. Prakash has extensive experience in machine learning, artificial intelligence, natural language processing, AI risk management, model governance.
Benika Hall (NVIDIA). Benika Hall is a senior solutions architect in the financial services area at NVIDIA. She focuses on generative AI and graph data science.
Dianqi Li (Citadel Securities).
Pusheng Zhang (Head of ML and AI at Cubist Systematic Strategies). Pusheng Zhang is the Head of Machine Learning and AI at Cubist Systematic Strategies, the quant arm of Point72 Asset Management, and bridges machine learning technology and quantitative trading for successful trading strategies. Prior to Cubist, Pusheng was a founding researcher and team lead of AI Research at Citadel, one of first AI research teams in the hedge fund industry. Before Citadel, Pusheng worked as a research and engineering leader at Uber and Microsoft.
Program Committe
Program Committe
Aboussalah, Amine M., New York University
Bhatia, Vrinda, Block
Cao, Haoyang, Johns Hopkins University
Cetingoz, Adil Rengim, Université Panthéon-Sorbonne (Paris I)
Chen, Ying, National University of Singapore
Chen, Yufan, University of Chicago
Cheng, Ziteng, The Hong Kong University of Science and Technology
Coache, Anthony, Imperial College London
Danait, Riya, University of Oxford
Desai, Abhi, New England College
Durand, Thibaut, Borealis AI
Galanti, Tomer, Texas A&M University - College Station
Golkhou, Zach, University of Washington
Grigoryan, Anna, BlackRock
Guhathakurta, Dipanwita, Georgia Institute of Technology
Gupta, Lavanya, J.P. Morgan Chase
Hou, Songyan, ETHZ - ETH Zurich
Huang, Yilie, Columbia University
Hwang, Yoontae, University of Oxford
Jia, Yanwei, The Chinese University of Hong Kong
Ji, Jingwei, Stanford University
Kaur, Rachneet, J.P. Morgan Chase
Li, Heyuan, University of California Berkeley
Li, Puheng, Amazon
Li, Xinyu, University of California, Berkeley
Lu, Kuan, Google
Ma, Yunshan, Singapore Management University
Mehta, Dhagash, BlackRock, Inc.
Nagasubramanian, Dhivya, University of Minnesota - Twin Cities
Ocello, Antonio, Ecole Nationale de la Statistique et de l'Administration Economique
Plank, Philipp, Imperial College London
Rafiey, Akbar, New York University
Reddy, Pavan, George Washington University
Song, Jae Wook, Hanyang University
Subramanian, Shankar, CUNY Brooklyn College
Sun, Zhongtian, University of Kent
Thompson, John R.J., University of British Columbia
Vadori, Nelson, J.P. Morgan AI Research
Visentin, Gabriele, ETHZ - ETH Zurich
Vittori, Edoardo, Intesa Sanpaolo
Vuletic, Milena, University of Oxford
Wang, Gaozhan, University of Southern California
Xu, Yumin, Peking University
Zhani, Juba, Georgia Institute of Technology
Zhang, Chao, Hong Kong University of Science and Technology
Zhang, Luhao, Johns Hopkins University
Zhang, Ruixun, Peking University
Zhang, Zixuan, Georgia Institute of Technology
Zhu, Fengbin, National University of Singapore
We are looking forward to seeing you at our workshop! 👋
We are looking forward to seeing you at our workshop! 👋
For questions, please contact:
For questions, please contact:
genaifinance2025@gmail.com
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