报告时间：2022年5月7日下午2:00-3:00
报告地点：腾讯会议
（会议ID：553 397 185）
报告嘉宾：高伟豪
报告主题：Machine Learning Meets Molecular Dynamics
报告摘要：
Machine Learning Meets Molecular Dynamics
Molecular Dynamics (MD) is a method to simulate the motion of molecular systems by Newtonian mechanics, which can be used to draw samples on the potential energy surface of the system and further compute macroscopic thermodynamic properties. MD is an important method to study the structure and properties of molecular systems, and has been widely used in chemical engineering, biomedicine, materials science, physics and other disciplines. Recently, machine learning techniques have been successfully introduced to increase the speed, accuracy and sampling efficiency of molecular dynamics. In this talk, I will introduce some recent work of ByteDance research on combining machine learning and molecular dynamics.
个人简介：
高伟豪，字节跳动研究科学家。本科就读于清华大学姚班，博士就读于伊利诺伊大学香槟分校电气与计算机工程系，于2019年获得博士学位，博士导师是Sewoong Oh教授和Pramod Viswanath教授。研究方向包括机器学习与分子模拟结合、机器学习、深度学习、推荐系统和信息论。在IEEE Transactions on Information Theory、ICML、NeurIPS等期刊和会议上发表论文十余篇。
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