Organization

Xiao-Yang Liu (Columbia University, Rensselaer Polytechnic Institute): Xiao-Yang Liu is now with the Department of Electrical Engineering at Columbia University and the Department of Computer Science at Rensselaer Polytechnic Institute. His research interests include Financial Large Language Models (FinLLM), Financial Reinforcement Learning (FinRL), tensor networks and high-performance tensor computation, and deep learning. He contributed chapters to two textbooks—Tensors for Data Processing, and Reinforcement Learning for Cyber-Physical Systems. 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.

Li Deng (Chief Al Officer at Vatic Investment; Former Chief Al Officer and Head of Machine Learning of Citadel; Former Chief Scientist of Al at Microsoft; Fellow of the lEEE and the Academy of Engineering of Canada; and close collaborator with Nobel Prize Laureate Geoffrey Hinton): Li Deng is the Chief AI Officer and Head of Machine Learning at Vatic Investments. He was previously the Chief AI Officer at Citadel, and the Chief Scientist of AI and Founder of the Deep Learning Technology Center at Microsoft. He has also been an Affiliate Professor at the University of Washington. His technical expertise includes Artificial Intelligence, Quantitative Finance, Portfolio Construction/Optimization, High Frequency Trading, Advanced Statistics and Machine Learning, Mathematical/Statistical Modeling, Applied Computer Science, Speech Recognition, Natural Language Processing, Deep Learning, Neural Networks, Big Data Analytics, and AI for education and healthcare. He received the 2019 IEEE SPS Industrial Leader Award" for leadership in pioneering research and development on large-scale deep learning that disrupted worldwide speech recognition industry and for leadership in natural language processing and finance engineering" and the 2015 IEEE SPS Technical Achievement Award "for outstanding contributions to deep learning and to automatic speech recognition." He was named a Canadian Academy of Engineering (CAE) Fellow in April 2019 in recognition for his research in deep learning and speech recognition. He authored/co-authored 6 technical books.

Z. Jane Wang (The University of British Columbia): Z. Jane Wang is a professor at the Department of Electrical and Computer Engineering at the University of British Columbia. She had been an Research Associate at the University of Maryland, College Park from 2002 to 2004. She is an IEEE Fellow, a Fellow of the Canadian Academy of Engineering (FCAE) and a member of the College of New Scholars, Artists and Scientists of the Royal Society of Canada. Her research interests are in the broad areas of signal/image processing and machine learning, with current focuses on digital media and biomedical data analytics. She has published 180+ journal papers and 120+ peer-reviewed conference papers. She has been a key Organizing Committee Member for numerous IEEE conferences and workshops (e.g., the co-Technical Chair for ICIP2021 and ICIP2025, and the co-General Chair of MMSP2018 and ICIP2026). She has been Associate Editor for the IEEE TSP, SPL, TMM, TIFS, TBME, and SPM, and as Editor-in-Chief for IEEE SPL.

Matt White (Executive Director of the PyTorch Foundation; GM of AI at the Linux Foundation): Matt White has nearly 30 years of experience in applied research and standards in AI and data in the telecom, media, and gaming industries. He began his career programming expert systems in the telecom industry and, since 2012, has been focused on machine learning and research at the intersection of AI, simulations, and multi-sensory learning. Mr. White is the Executive Director of the PyTorch Foundation, the GM of AI at the Linux Foundation, the Director of the Linux Foundation’s Generative AI Commons, and the Co-founder and Chair of the Open Metaverse Foundation at the Linux Foundation. He is a Chair at the Metaverse Standards Forum, founded the Silicon Valley Generative AI paper reading group, and is a co-organizer at the GenAI Collective.