BIMSA >
BIMSA-HSE Joint Seminar on Data Analytics and Topology
Statistics at a crossroads: How it can revolutionize artificial intelligence
Statistics at a crossroads: How it can revolutionize artificial intelligence
演讲者
时间
2025年03月03日 20:00 至 21:00
地点
A6-101
线上
Zoom 468 248 1222
(BIMSA)
摘要
Artificial intelligence (AI) is profoundly impacting science and society by applying algorithms and machine learning to enable machines to perform humanlike tasks. Statistics as a branch of mathematics, lying at the core of AI and data science, is facing an unprecedented challenge with the surge of complex, heterogenous data across a variety of platforms. In a real sense, statistics is at a crossroads to leverage its central role in revolutionizing the foundational and fundamental framework of AI. In this talk, I will present several state-of-the-art statistical methods that have been widely used in AI across various fields. I will focus on how to develop statistically principled reasoning and theory to validate the application of AI and enhance its interpretability and sustainability. Our approach builds on statistical mechanics theory and methodology derived from interdisciplinary integration.
演讲者介绍
邬荣领，1995年获美国华盛顿大学（西雅图）数量遗传学博士学位，曾任美国宾夕法尼亚州立大学统计学、公共卫生科学杰出教授，统计遗传研究中心主任，现任北京雁栖湖应用数学研究院研究员、清华大学丘成桐数学研究中心曾思明讲座教授，同时担任遗传学、生物信息学、计算生物学领域多家期刊主编、副主编、特约编辑和编委。入选美国科学促进会会士、美国统计学会会士，获美国应用数学与统计研究院（SAMSI）杰出研究员奖、佛罗里达大学研究基金教授奖、宾夕法尼亚州立大学杰出大学教授奖、Floyd科学创新等。研究兴趣包括：发展跨学科统计方法，揭示复杂性状及人类复杂疾病的遗传控制机理。提出的功能作图(Functional mapping)方法能有效发现性状发育的遗传规律，刻画基因效应随时空变化的关键模式。将功能作图与进化博弈论、尺度理论、食饵-捕食者理论相结合，发展出一系列计算方法用于构建从分子到表型的多层次、多空间、多刻度的基因型-表型关系立体网络，为系统生物学、系统医学、系统药物学研究提供分析工具。在Nature Reviews Genetics、Nature Communications、PNAS、Journal of the American Statistical Association、Annals of Applied Statistics、Physics of Life Reviews、Physics Reports、Briefings in Bioinformatics、Cell Reports、Evolution等国际重要刊物上发表SCI论文逾400篇，研究成果被Science、Cell等重要刊物引用或重点介绍。