第十届“中国人民大学国际统计论坛”（RUC IFS 2025）将于2025年7月4-6日在中国人民大学召开。大会邀请美国、澳大利亚等国家和地区的知名学者参会，将就“统计学发展史、数理统计、数据科学与人工智能、生物统计学前沿探究、政府统计、金融统计”等问题展开深入交流与讨论。

本次介绍特邀报告人Zhu, Hongtu，报告主题为“Conditional Distributional Learning with Non-crossing Quantile Network and applications”。

Zhu, Hongtu

Title

Conditional Distributional Learning with Non-crossing Quantile Network and applications

Abstract

We introduce the Non-Crossing Quantile (NQ) Network, a novel approach for conditional distribution learning. By incorporating non-negative activation functions, the NQ network ensures monotonicity in learned distributions, effectively eliminating the issue of quantile crossing.  The NQ network offers a highly adaptable deep distributional learning framework, applicable to a wide range of tasks, from non-parametric quantile regression to causal effect estimation and distributional reinforcement learning (RL). We further establish a comprehensive theoretical foundation for the deep NQ estimator and its application indistributional RL, providing rigorous analysis to support its effectiveness. Extensive experiments demonstrate the robustness and versatility of the NQ network across various domains, including clinical trials, e-commerce, games, and healthcare, highlighting its potential for real-world applications. This is based on a series of joint works with Drs. Shen, Luo, and Shi and Mr. Huang.

Biography

Dr. Hongtu Zhu is the Kenan distinguished professor of biostatistics, statistics, radiology, computer science, and genetics at the University of North Carolina at Chapel Hill. He was a DiDi Fellow and Chief Scientist of Statistics at DiDi Chuxing between 2018 and 2020 and held the Endowed Bao-Shan Jing Professorship in Diagnostic Imaging at MD Anderson Cancer Center between 2016 and 2018. He is an internationally recognized expert in statistical learning, medical image analysis, precision medicine, biostatistics, artificial intelligence, and big data analytics. He received an established investigator award from the Cancer Prevention Research Institute of Texas in 2016, the INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice in 2019,  and the COPSS 2025 Snedecor Award. He has published more than 340 papers in top journals, including Nature, Science, Cell, Nature Genetics,   PNAS,  AOS, JASA, Biometrika, and JRSSB, as well as presenting 55+ conference papers at top conferences, including meetings for Neurips, ICLR, ICML, AAAI, and KDD. He is the coordinating editor of JASA and the editor of JASA ACS.