报告人：王梦泽 助理教授 （香港城市大学）  

报告内容：

 Numerical simulations of chaotic and multiscale systems, such as engineering turbulence and global climate, present significant challenges. Even at the highest level of simulation fidelity, due to the assumptions introduced in initial condition or model parameters, numerical predictions often deviate from experimental measurements. Data assimilation provides a systematic framework to address these limitations by optimally infusing observations into numerical simulations, enabling the full access to all the scales. In this talk, I will first focus on canonical wall-bounded turbulence. Given sparse velocity data, our objective is to construct a Navier-Stokes solution that reproduces these observations and predict the unknown flows. A critical data resolution is identified that ensures an accurate reconstruction of turbulence. Below this critical threshold, only the flows within the domain of dependence of observations can be accurately decoded. I will then address the more challenging scenario of biased model equations, using climate simulations as an example. A prediction-correction strategy will be presented, where data assimilation is utilized to nudge the simulations towards observations. These aligned simulationobservation pairs are then used to train a machine-learning model that identifies and removes systematic biases. When applied to free-running climate simulations, this framework demonstrates significant improvements in capturing the statistics of extreme events. 

报告人简介：

Mengze Wang is a Presidential Assistant Professor in the Department of Mechanical Engineering at the City University of Hong Kong. Before joining CityUHK in 2026, he was a Postdoctoral Researcher at Massachusetts Institute of Technology, since 2023. He received his Ph.D. in Mechanical Engineering from Johns Hopkins University (2022) and B.Sc. in Theoretical and Applied Mechanics from Peking University (2016). His research focuses on developing data assimilation and machine learning methods for high-dimensional dynamical systems, with applications in aerospace engineering and geophysical flows.

主持人：陈正 教授（北京大学应用物理与技术研究中心）

时  间：2026年4月29日（周三）12:20

地  点：北京大学工学院1号楼210会议室