Symposium2025-STA,CUHK

Saturday, December 20, 2025 (Hong Kong Time)
08:00 – 08:30	Registration + Photo Taking at the Backdrop
08:30 – 08:55	Opening Ceremony
08:55 – 09:00	Group Photo
Session Chair: Professor Xiaodan Fan (The Chinese University of Hong Kong)
09:00 – 09:45	Keynote Lecture Professor Jun Liu (Tsinghua University / Harvard University) AI Deployment and Statistical Thinking
Session Chair: Professor Tony Sit (The Chinese University of Hong Kong)
09:45 – 10:45	Industrial Talks Mr. Chi Ho Chan (Census and Statistics Department, HKSAR) Smart Statistics: C&SD’s Digital Transformation in the AI Era Dr. Pengcheng Chen (Sina Corporation) Statistical Decision in Financial Risk Management Mr. Ted Yu (The Hongkong and Shanghai Banking Corporation Limited) Leveraging AI and Data Science for Risk Management in Banking
10:45 – 11:05	Coffee Break
Session Chair: Professor Huichen Zhu (The Chinese University of Hong Kong)
11:05 – 11:50	Keynote Lecture Professor Heping Zhang (Yale University) Unadorned Statistics in the Light of AI
11:50 – 12:35	Keynote Lecture Professor Fang Yao (Peking University) Deep Semiparametric Partial Differential Equation Models
12:35 – 14:30	Lunch (By Invitation )
Session Chair: Professor Gen Li (The Chinese University of Hong Kong)
14:30 – 15:15	Keynote Lecture Professor Todd Ogden (Columbia University) Functional Metric Learning for Classification Problems
15:15 – 16:00	Keynote Lecture Professor Yuxin Chen (The Wharton School, The University of Pennsylvania) Transformers Meet In-Context Learning: A Universal Approximation Theory
16:00 – 16:20	Coffee Break
Session Chair: Professor Gen Li (The Chinese University of Hong Kong)
16:20 – 16:50	Professor Jie Ding (University of Minnesota) Designing Intelligent AI: Insights from Human Cognition
16:50 – 17:20	Professor Jingyuan Liu (Xiamen University) LLM-Powered Deep Panel Modeling
17:20 – 17:50	Professor Gen Li (The Chinese University of Hong Kong) Faster Convergence and Acceleration for Diffusion-Based Generative Models
18:30	Banquet (By invitation)

Sunday, December 21, 2025 (Hong Kong Time)
Session Chair: Professor Jiacheng Zhang (The Chinese University of Hong Kong)
09:00 – 09:45	Keynote Lecture Professor Xin Guo (University of California, Berkeley) From LLM to RL and Diffusion Models, via (rough) Differential Equations
09:45 – 10:30	Keynote Lecture Professor Henry Lam (Columbia University) Bootstrap with Very Few Resamples: An Integrative View on Data and Monte Carlo Uncertainties
10:30 – 10:50	Coffee Break
Session Chair: Professor Jiacheng Zhang (The Chinese University of Hong Kong)
10:50 – 11:20	Professor Chi Seng Pun (Nanyang Technological University) Backward Stochastic Volterra Integral Equations with General Nonlinearities
11:20 – 11:50	Professor Mathieu Lauriere (New York University Shanghai) An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control
11:50 – 12:20	Professor Jiacheng Zhang (The Chinese University of Hong Kong) Continuous-time Mean Field Games: A Primal-dual Characterization
12:20 – 14:30	Lunch (By Invitation )
Session Chair: Professor Yingxin Lin (The Chinese University of Hong Kong)
14:30 – 15:15	Keynote Lecture Professor Xuegong Zhang (Tsinghua University) Large AI Cellular Models: Promises and Challenges
15:15 – 16:00	Keynote Lecture Professor Qi Long (University of Pennsylvania) Responsible Statistical and AI/ML Methods for Harnessing the Power of Electronic Health Records
16:00 – 16:20	Coffee Break
Session Chair: Professor Yingxin Lin (The Chinese University of Hong Kong)
16:20 – 16:50	Professor Linbo Wang (University of Toronto) Fighting Noise with Noise: Causal Inference with Many Candidate Instruments
16:50 – 17:20	Professor Qiongshi Lu (University of Wisconsin–Madison) The Blurred Line Between Genes and Environments: Insights from GWAS of Family Members’ Phenotypes
17:20 – 17:50	Professor Yingxin Lin (The Chinese University of Hong Kong) Controlling False Discoveries after Clustering via Data Splitting for Spatial Domain Marker Detection
17:50 – 17:55	Closing Remarks Professor Xinyuan Song (The Chinese University of Hong Kong)