Organizers

Core Organizers

Photo	Biography
	Keyi Wang, (Leader) master at Northwestern University, bachelor at Columbia University. Organizer of FinRL Contest 2023 and FinRL Contest 2024 at ACM ICAIF conferences, and Regulations Challenge at COLING 2025. Interested in machine learning and financial engineering. Research assistant at GenAI Research on Open Finance at Columbia University.
	Jiechao Gao, Ph.D., University of Virginia. His research interests include machine learning, reinforcement learning, federated learning algorithms and applications in distributed networks, cyber-physical systems, cloud computing and financial environment. He serves as PC member and reviewer for NeurIPS, KDD, AAAI, INFOCOM, IEEE Big Data, IEEE TNNLS, IEEE IoT Journal, etc.
	Yupeng Cao, current Ph.D. candidate in the Electrical and Computer Engineering Department at Stevens Institute of Technology. His research interests include Natural Language Processing (NLP), Multimodal, Trustworthy AI, and their application in the financial domain. He has several publications about multimodal, LLMs, and multi-agent in financial domains, including FinNLP workshop, ICAIF, ACL, and NeurIPS. He served as a PC member for the 9th FinNLP workshop and Session Chair @ACM ICAIF’24. He organized the Agent-Based Single Cryptocurrency Trading Challenge @COLING 2025. He also hosted the “TechFin” social event at NeurIPS 2024, with 100+ participants.
	Mostapha Benhenda, (Task 1: FinRL-DeepSeek) PhD, Sorbonne Paris North University. Current interests include reinforcement learning, large language models and their applications to computational finance and automated trading. Core team member of AI4Finance Foundation.
	Arnav Grover, (Task 1: FinRL-DeepSeek) Bachelor’s in Computer Science @ Purdue University. Researching at the intersection of responsible AI governance, alignment, and quantitative finance. Committed to developing AI systems that are ethically robust, transparent, and beneficial to society.
	Colin Lin, (Task 2: FinAgents) Master’s student in Electrical and Computer Engineering at Carnegie Mellon University, Bachelor of Science in Computer Science from Rensselaer Polytechnic Institute. Lead organizer of the Open FinLLM Leaderboard initiative, driving the integration of regulatory reporting benchmarks including CDM, MOF and XBRL frameworks. Author of “Analyzing Cascading Outbreak of GameStop Event: A Practical Approach Using Network Analysis and Large Language Models” presented at ICAIF 2024. Contributor to AI4Finance open-source ecosystem with focus on reinforcement learning applications in financial LLM development.
	Jaisal Patel, (Task 2: FinAgents) undergraduate at Rensselaer Polytechnic Institute. Interested in quantitative finance, venture capital, and the intersection of AI and finance. Program committee member for the International Workshop on Multimodal Financial Foundation Models (MFFMs) at ICAIF 2024. Only student award recipient at GitHub Universe 2023.
	Sarah Huang, (Task 2: FinAgents) master’s graduate from Columbia University and Bachelor’s from Barnard College. Research Assistant at the Open Finance Lab at Columbia University, focusing on AI applications in risk management and compliance. Passionate about AI-driven solutions in enterprise risk management and finance.
	Yan Wang, (Task 2: FinAgents) Yan Wang is a Postdoctoral Associate at Yale University, specializing in biomedical, clinical, and financial natural language processing (NLP). His research focuses on text mining, information extraction, and information retrieval using large language models (LLMs), as well as reasoning model training and retrieval-augmented generation (RAG) framework development. Dr. Wang regularly serves as a reviewer for several top conferences and journals, including BIBM, AMIA, NeurIPS, COLING, EMNLP, Information Sciences, Bioinformatics, and Journal of Biomedical Informatics.
	Yang Ren, (Task 2: FinAgents) Yang Ren, Ph.D., is a Postdoctoral Associate at Yale University. He received his Ph.D. from the University of South Carolina. His research focuses on natural language processing and large language models, with applications in healthcare and finance. He is a member of the FinAI Working Group and serves as a reviewer for JMIR, IJMI, ICML, ICLR, and KDD.
	Alessio Brini, (Task 3: DeFi LP) Dr. Alessio Brini is a faculty member at Duke University’s Pratt School of Engineering and leads the Digital Asset Research & Engineering Collaborative (DAREC). His expertise lies in applying machine learning and data science to digital assets, decentralized finance (DeFi), and financial challenges. Alessio holds a Ph.D. in Mathematical Finance from Scuola Normale Superiore (Italy) focusing on reinforcement learning for finance. At Duke, he teaches courses in Machine Learning for FinTech, Data Wrangling, and Statistics while mentoring students through Capstone projects and research. His work has earned recognition through published research, conference presentations, and active contributions to the academic community.

Advisors

Photo	Biography
	Xiao-Yang Liu, Ph.D., Columbia University. His research interests include deep reinforcement learning, big data, and high-performance computing. He created several open-source projects, such as FinRL, ElegantRL, and FinGPT. He contributed chapters to a textbook on reinforcement learning for cyber-physical systems and a textbook on tensors for data processing. He serves as a PC member for NeurIPS, ICML, ICLR, AAAI, IJCAI, AISTATS, and ICAIF. He also served as a Session Chair for IJCAI 2019. He organized Financial Challenges in Large Language Models (FinLLM)@IJCAI 2024, FinRL Competition at ACM ICAIF 2023, the First/Second Workshop on Quantum Tensor Networks in Machine Learning (QTNML) at NeurIPS 2020/2021, IJCAI 2020 Workshop on Tensor Networks Representations in Machine Learning, and the NeurIPS 2019 Workshop on Machine Learning for Autonomous Driving.
	Kairong Xiao, Roger F. Murray Associate Professor of Business at Columbia Business School. His research interests span financial intermediation, corporate finance, monetary economics, industrial organization, and political economy. His research papers have been published in top finance and economics journals, including the Journal of Finance, the Review of Financial Studies, the Journal of Financial Economics, Econometrica, the Journal of Monetary Economics, and Management Science. He received numerous awards for research excellence, including the Review of Financial Studies Rising Scholar Award, the Journal of Finance Dimensional Fund Advisors Prize for Distinguished Paper, and the Review of Financial Studies Best Paper Award runner-up.

Photo

Biography

Xiao-Yang Liu, Ph.D., Columbia University. His research interests include deep reinforcement learning, big data, and high-performance computing. He created several open-source projects, such as FinRL, ElegantRL, and FinGPT. He contributed chapters to a textbook on reinforcement learning for cyber-physical systems and a textbook on tensors for data processing. He serves as a PC member for NeurIPS, ICML, ICLR, AAAI, IJCAI, AISTATS, and ICAIF. He also served as a Session Chair for IJCAI 2019. He organized Financial Challenges in Large Language Models (FinLLM)@IJCAI 2024, FinRL Competition at ACM ICAIF 2023, the First/Second Workshop on Quantum Tensor Networks in Machine Learning (QTNML) at NeurIPS 2020/2021, IJCAI 2020 Workshop on Tensor Networks Representations in Machine Learning, and the NeurIPS 2019 Workshop on Machine Learning for Autonomous Driving.

Kairong Xiao, Roger F. Murray Associate Professor of Business at Columbia Business School. His research interests span financial intermediation, corporate finance, monetary economics, industrial organization, and political economy. His research papers have been published in top finance and economics journals, including the Journal of Finance, the Review of Financial Studies, the Journal of Financial Economics, Econometrica, the Journal of Monetary Economics, and Management Science. He received numerous awards for research excellence, including the Review of Financial Studies Rising Scholar Award, the Journal of Finance Dimensional Fund Advisors Prize for Distinguished Paper, and the Review of Financial Studies Best Paper Award runner-up.