To Bridge the Gap Between AI and Finance
Organizers
Speaker
Time
Monday, December 8, 2025 2:35 PM - 3:15 PM
Venue
A6-101
Online
Zoom 388 528 9728
(BIMSA)
Abstract
This talk will focus on the interdisciplinary area of machine learning and finance. Machine learning in finance has unique characteristics. Directly applying existing machine learning models is easy, but not good enough. I will explore the following finance research topics with machine learning: Tail Modeling and Risk Management, Portfolio Optimization, and Financial Derivatives. Besides, this talk will aslo cover some general machine learning topics, such as Uncertainty Quantification and Out-of-Distribution (OOD) Generalization.
Speaker Intro
I have been an Associate Professor at BIMSA since 2025. Prior to this role, I was an Assistant Professor at the Institute of Statistics and Big Data, Renmin University of China. My research lies at the intersection of AI and finance/business, focusing on FinTech and Business Analytics through innovative machine learning and data science methodologies. My interests include tail risk management, empirical asset pricing, portfolio optimization, derivatives, consumer credit, and related areas. Recently, I have also developed an interest in out-of-distribution (OOD) generalization and uncertainty quantification in machine learning. I publish in both finance/business and machine learning academic journals and conferences.
I am seeking highly self-motivated Postdoctoral researchers or research interns to conduct high-quality research in the areas of AI, digital economy, or applied mathematics. If you are interested, please feel free to contact me.
I am seeking highly self-motivated Postdoctoral researchers or research interns to conduct high-quality research in the areas of AI, digital economy, or applied mathematics. If you are interested, please feel free to contact me.