Abstract

Many problems in applied sciences can be abstractly formulated as systems navigating over complex energy landscapes. Well-known examples include conformational changes of bio-molecules, chemical reactions, nucleation events during phase transitions, and extreme events in some cases that lead to material or system failure, etc. These events happen infrequently relative to the relaxation timescale of the system, but when they do happen, they usually happen rather quickly and have important consequences. In this talk, I will discuss numerical methods for the study of such rare events, including the string method and the recently developed machine learning techniques.

Biography：

任维清，新加坡国立大学教授，2002年毕业于纽约大学Courant数学科学研究所并获博士学位。先后在普林斯顿高等研究院和普林斯顿大学从事博士后研究工作，2005年至2011年在纽约大学Courant数学科学研究所担任助理教授。任教授的研究领域主要为稀有事件模型，多尺度问题的理论和数值方法，以及多相流体动力学。任教授曾获Alfred P. Sloan Research Fellowship (2007) 和冯康科学计算奖（2015）。