Events
Global AI Frontier Lab Panel Discussion: AI in Finance
Speaker: Kyunghyun Cho, Hong Li, Dmitry Malioutov, Tim Schwider, Marc Pavese
Location: 1 MetroTech Center, Room Global AI Frontier Lab (Floor 22)
Date: Monday, November 2, 2026
We are pleased to invite you to a panel discussion on AI in Finance at the Global AI Frontier Lab on November 2, 2026. Check in will begin at 5:00 PM EST and the panel discussion will start at 5:30 PM EST followed by a reception. The Global AI Frontier Lab is located on the 22nd floor at 1 Metrotech Center, Brooklyn, NY 11201.
Featured Panelists:
Kyunghyun Cho
Professor & Global AI Frontier Lab Co-Director, New York University
Co-Founder & CEO, Ortet
Bio: Kyunghyun Cho is a co-founder and CEO of Ortet and the Glen de Vries Professor of Health Statistics and a professor of computer science and data science at New York University. He is also a CIFAR Fellow of Learning in Machines & Brains and an Associate Member of the National Academy of Engineering of Korea. In early 2021, he co-founded Prescient Design which was acquired by Genentech in late 2021. Since then, he served as an Executive Director of Frontier Research and a Senior Fellow at Genentech until January 2026. He served as a Co-Program Chair of ICLR 2020, NeurIPS 2022, and ICML 2022 and also on the boards of ICML and ICLR. He was one of the three founding Editors-in-Chief of the Transactions on Machine Learning Research (TMLR) until 2024. He was a research scientist at Facebook AI Research from June 2017 to May 2020 and a postdoctoral fellow at University of Montreal until Summer 2015 under the supervision of Prof. Yoshua Bengio, after receiving MSc and PhD degrees from Aalto University April 2011 and April 2014, respectively, under the supervision of Prof. Juha Karhunen, Dr. Tapani Raiko, and Dr. Alexander Ilin. He received the Samsung Ho-Am Prize in Engineering in 2021. He tries his best to find a balance among machine learning, natural language processing, and life, but almost always fails to do so.
Hong Li
Former Managing Director & Head of Quantitative Research, Americas, Citi
Bio: Hong Li recently retired from Citi where he was Managing Director and Head of Quantitative Research, Americas. He began his Wall Street career as an equity analyst at Salomon Brothers in 1997. He holds both a Ph.D. and an M.B.A. from the Booth School of Business at the University of Chicago. He has published numerous peer-reviewed articles in academic and industry journals, including the Journal of Portfolio Management, Risk Magazine and the Journal of American Statistical Association.
Dmitry Malioutov
Previous Director of Portfolio Management & Machine Learning Applications in Quant Macro, WorldQuant LLC
Bio: Dmitry Malioutov most recently served as Director of Portfolio Management and Machine Learning Applications in Quant Macro at WorldQuant LLC and will soon join the AI Core Group at Two Sigma Investments. His career spans quantitative finance and industrial research, with previous roles at D. E. Shaw, DRW Trading, IBM Research, and Microsoft Research. In quantitative finance, Dmitry has worked across a broad range of trading horizons and strategies, from high-frequency trading and intraday statistical arbitrage to daily-horizon quantitative macro strategies. He holds an MS and PhD from MIT. His research interests include time-series forecasting, risk modeling and portfolio construction, interpretable ML, probabilistic graphical models, high-dimensional estimation, and sparse signal processing.
Dmitry has served on program committees for leading machine learning conferences, including NeurIPS, ICML, and ICLR, and as an associate editor for IEEE journals, including IEEE Transactions on Signal Processing. He also served as an editor of a Wiley volume on Financial Machine Learning and Signal Processing.
Tim Schwider
Senior Managing Director & Head of Quantitative Research, Lord, Abbett & Co LLC
Bio: Tim Schwider is responsible for overseeing a team of researchers who develop quantitative models and techniques to conduct portfolio risk analysis and security valuation for Lord Abbett’s equity portfolios. Mr. Schwider joined Lord Abbett in 2019. Prior to his current role, he served as a Quantitative Analyst responsible for building portfolio risk models and security valuation tools for use across all investment strategies. His previous experience includes serving as Partner, Portfolio Manager at AlphaCrest Capital; Director, Portfolio Manager at Credit Suisse Asset Management; Vice President, ProprietaryTrader at J.P. Morgan Securities and Quantitative Analyst at Goldman Sachs/The HullGroup. He has worked in the financial services industry since 1998. He earned a BS in mathematics from Harvey Mudd College and a Ph.D. in mathematics from the University of Michigan.
Moderated by:
Marc Pavese
Global AI Frontier Lab Advisory Council Member
Retired Partner & Former Head of Quantitative Research & Technology, Lord, Abbett & Co LLC
Bio: Marc Pavese, PhD, is a scientist, investor, data and analytics expert, and technology leader with more than 25 years of experience conducting computational research, developing advanced analytics, and deploying machine learning systems in real-world decision environments. Mr. Pavese is a retired Partner at Lord Abbett, a $250B diversified asset manager, where he served as Head of Quantitative Research, Analytics & Technology, leading a multidisciplinary organization of researchers, analysts, data engineers, machine learning specialists, and software developers. He also served on several of the firm’s senior governing bodies during his tenure at Lord Abbett, including the Executive, Operating, and Investment Committees. Pavese is currently an advisor and consultant on AI, data analysis, and technology. He also serves as a member of the Advisory Council of the NYU Global AI Frontier Lab, and as an Executive-in-Residence at Columbia Technology Ventures. Pavese received his PhD in Theoretical Physical Chemistry from the University of Pennsylvania and his BA in Chemistry from Columbia University.
Please reach out to global-ai-frontier-lab@nyu.edu with any questions. We hope to see you there!