The International Conference on emerging aspects of kinetic theory, nonlocal equations, and related applications

Conference introduction:

Advances in kinetic theory have revolutionized the analysis and simulation of many- particle systems, which are prevalent in both nature and engineering.  This conference aims to foster the development of new theoretical and computational tools in the field of kinetic and nonlinear nonlocal equations, while also exploring the application of these models in diverse scientific disciplines.

Kinetic equations describe the collective behavior of many-particle systems, enabling the extraction of macroscopic or average information.   They bridge the gap between microscopic systems, which are modeled using stochastic or deterministic ODEs, and macroscopic continuum descriptions, including hyperbolic, diffusive, or hydrodynamic equations. To date, kinetic theory has become an essential tool for studying a wide range of phenomena in fields such as plasma physics, semiconductors, quantum gases, animal swarms, and other physical and biological processes. More recently, it has also played a crucial role in the advancement of theoretical machine learning.  Despite its importance, the interplay between long- and short-range interactions, transport and diffusion, and their nonlocal and nonlinear features presents significant mathematical challenges. These challenges are central to understanding equilibrium states, the stability of patterns, and their asymptotic behavior.   Additionally,  developing efficient  computational methods that address high dimensionality while preserving key structures remains a difficult task.

On the other hand, new tools such as optimal transport and, more broadly, the cal- culus of variations, have significantly advanced the study of kinetic theory and nonlocal equations. These methods enhance our understanding of long-time asymptotics for non- linear diffusion equations and interaction models, while also facilitating the development of structure-preserving numerical schemes.  In addition, scientific machine learning has emerged as a promising tool for tackling high-dimensional problems, already making a significant impact on kinetic simulations.

The aim of this workshop is to bring together leading experts in kinetic and nonlocal equations to explore a wide range of topics.  These include the quantitative analysis of equations and their solution properties, such as free energy minimization, well-posedness, regularity, and long-time asymptotics, as well as the development of efficient, structure- preserving numerical methods, stochastic methods and their applications.  Furthermore, we aim to foster meaningful dialogue between theoretical and numerical experts in the field to advance both areas through collaborative efforts.

Time: July.20-25, 2025

Venue: Nanshan Yisuo, East Lake Hotel(东湖宾馆南山乙所

Address:East Lake Hotel ,142 Donghu Rd ,Wuchang District, Wuhan, Hubei, China

⟡  Organizing committee

J. A. Carrillo (University of Oxford, UK),

L. Wang (University of Minnesota, USA),

T. Yang (Wuhan University, China),

H. Zhao (Wuhan University, China)

Speakers

Andrea MedagliaUniversity of Oxford, UK
Andrew ChristliebMichigan State, USA
Chaozhen WeiUniversity of Electronic Science and Technology of China, China
Francis FilbetUniversite de Toulouse, France
Hui HuangUniversity of Graz, Austria
James RossmanithIowa State University, USA
Lorenzo PareschiHeriot-Watt University, UK
Lukas EinkemmerUniversity of Innsbruck, Austria
Maxime HerdaUniversite de Lille, France
Min TangShanghai Jiao Tong University, China
Ning JiangWuhan University, China
Pan Pan RenCity University of Hong Kong, China
Qi WangSouthwestern University of Finance and Economics, China
Qin LiUniversity of Wisconsin-Madison, USA
Renjun DuanChinese University of Hong Kong, China
Ruo LiPeking University, China
Shi JinShanghai Jiao Tong University, China
Shuangqian LiuCentral China Normal University, China
Weiran SunSimon Fraser University, Canada
Weixi LiWuhan University, China
Yoshiyuki KageiTokyo Institute of TechnologyJapan
Yunan YangCornell University, USA
Zhenfu WangPeking University, China
Zhennan ZhouWestlake University, China
Zhenning CaiNational University of Singapore, Singapore
Zhiwen ZhangUniversity of HongKong, China
Zhu ZhangThe Hong Kong Polytechnic University, China

⟡  Schedule:

⟡  Sponsors:

 Tianyuan Mathematical Center in Central China

 Institute for Math & AI, Wuhan

   School of Mathematics and Statistics,Wuhan University

Contact:

Lingling Tang        tmcc@whu.edu.cn

Jingnan Zhang       zjn1105@whu.edu.cn

近期会议