Organizers

Core Organizers

Photo	Biography
	Colin Lin, (Leader) Research Assistant at SecureFinAI Lab, Columbia University. Master’s student in Electrical and Computer Engineering at Carnegie Mellon University, Bachelor of Science in Computer Science from Rensselaer Polytechnic Institute. Leading project: Evaluation and Benchmarking Suite for Financial LLMs and Agents. 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.
	Keyi Wang, (Leader) Master’s at Northwestern University, Bachelor’s at Columbia University. Research Assistant at SecureFinAI Lab at Columbia University. Organizer of FinAI Contest 2025 at IEEE CSCloud, FinRL Contest 2025 at IEEE IDS, FinRL Contest 2024 and FinRL Contest 2023 at ACM ICAIF conferences, and Regulations Challenge at COLING 2025. Reviewer of ACM ICAIF conferences. Interested in machine learning and financial engineering.
	Jiechao Gao, Jiechao is currently a Postdoctoral Research Scientist at Stanford University. His research interests include machine learning, large-scale foundation models, interpretability, reinforcement learning, federated learning algorithms, and applications in distributed networks, cyber-physical systems, cloud computing, and financial environments. He has served as an Area Chair, Program Committee, and reviewer for leading conferences and journals such as NeurIPS, ICML, ICLR, KDD, AAAI, IJCAI, IEEE TNNLS, IEEE IoT Journal, etc. He has also actively contributed to community building, serving as Organizer of FinAI Contest 2025 at IEEE CSCloud, FinRL Contest 2025 at IEEE IDS, and FinRL Contests 2023–2024 at ACM ICAIF. In 2024 and 2025, he was recognized in the Stanford Elsevier Top 2% Scientist list.
	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.
	Sally Liu, (Task 1) undergraduate at Columbia University. Her research interests include machine learning and reinforcement learning, with applications in science and finance.
	Chunlin Feng, (Task 1) undergraduate at Rensselaer Polytechnic Institute with research interests reinforcement learning and its applications in finance, focusing on market environments.
	Lijian Huang, (Task 1) undergraduate at Rensselaer Polytechnic Institute. He contribute to Standard Market Environments for Financial Reinforcement Learning and Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations as co-author. He contribute to Classical Simulation of Quantum Circuits Using RL as Research Assistant.
	Jaisal Patel, (Task 1 & 2) 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.
	Lingfei Qian, (Task 3). Lingfei is a Postdoctoral Associate at the Section of Biomedical Informatics and Data Science, Yale School of Medicine. His research focuses on machine learning, natural language processing, and multimodal financial data analysis, with a particular emphasis on RAG (retrieval-augmented generation) and multi-agent LLM frameworks. He is passionate about developing AI-driven solutions for real-world financial challenges, including trading, risk management, and decision-making, and has led the design of benchmarks and systems that connect advanced language models with practical financial applications.
	Xueqing Peng (Task 3) Xueqing is a Postdoctoral Associate in the Department of Biomedical Informatics and Data Science, Yale School of Medicine. She received her Ph.D. from Fudan University. Her research focuses on natural language processing, large language models, and domain-specific AI, with applications in finance and biomedicine. She is particularly interested in multilingual and multimodal benchmarks, trustworthy LLM evaluation, and methods for analyzing scientific novelty and innovation. She also serves as a reviewer for Clinical and Experimental Medicine and JMIR Medical Informatics, and helped organize the FinNLP-FNP-LLMFinLegal workshop at COLING 2025.

Local Organizers

Photo	Biography
	Nuo Chen, Ph.D. student in the School of Computing at the National University of Singapore, advised by Prof. Bingsheng He. His research interest lies in Large Language Model (LLM) engineering, particularly in unlocking their potential for practical applications (LLM as a judge & a researcher). His representative works include those on large reasoning models as a judge and diagnosing the crisis of AI conferences.
	Qian Wang, third-year Ph.D. candidate in Computer Science at the National University of Singapore, advised by Prof. Bingsheng He. Her research focuses on LLM-based Multi-Agent Systems, Trustworthy AI, and cryptocurrency-related applications. She has authored four first-author papers accepted by top conferences such as COLM, ACL, EMNLP, ICLR, and has received multiple academic awards, including the NUS Research Achievement Award and the Venture Initiation Program@SoC Grant.

Advisors

Photo	Biography
	Xiao-Yang Liu, Ph.D. candidate, Director of SecureFinAI Lab, Columbia University. His research interests include deep reinforcement learning, big data, and high-performance computing. He created several open-source projects, such as FinRL 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.
	Jimin Huang, the founder of The Fin AI working group, an initiative dedicated to advancing open science, tooling, and model development for the financial services industry with a focus on responsible innovation. The Fin AI is now an associated member of FINOS and a collaborator with the NVIDIA AI Technology Center (NVAITC) through Hugging Face. Jimin is also an associated member of The National Centre for Text Mining (NaCTeM). His research spans natural language processing and computational finance, with a particular emphasis on financial large language models (LLMs) and open-source contributions. He is the organizer of the FinLLM Challenge at FinNLP-AgentScen @ IJCAI-2024 and serves as the general chair for The Joint Workshop of the 9th Financial Technology and Natural Language Processing (FinNLP), the 6th Financial Narrative Processing (FNP), and the 1st Workshop on Large Language Models for Finance and Legal (LLMFinLegal).