3/16 Seminar Speech

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上層分類：News

分類：Speeches

建立於 2020-03-09, 週一 16:21

最近更新於 2020-03-16, 週一 13:22

發佈於：2020-03-09, 週一 16:22

點擊數：4427

Speaker: Professor Chun-Wei Pao

Topic: Application and Challenge of Machine Learning in Atomic-scale Simulation

Speaker：Professor Chun-Wei Pao

Organization：Research Center for Applied Sciences, Academia Sinica

Topic：Application and Challenge of Machine Learning in Atomic-scale Simulation

Date：10:20 , 2020.3.16

Location：Room 203, College of Engineering

Education：

Princeton University (U.S.A.) / Department of Mechanical and Aerospace Engineering / PhD

National Taiwan University / Institute of Applied Mechanics / MS

National Tsing Hua University / Department of Power Mechanical Engineering / BS

Work Experience：

National Chiao Tung University / Department of Photonics / Adjunct Professor

National Dong Hwa University / Department of Materials Science and Engineering / Adjunct Professor

Academia Sinica / Research Center for Applied Sciences / Research Fellow

Los Alamos National Laboratory (U.S.A.) / Theoretical Division / Post-doctoral Research Associate

Abstract：

Machine learning has drawn significant amount of attentions around the world because of their capability of building predictive models that are difficult to be extracted solely by human brains. In this talk, I will talk about application of machine learning models on atomistic simulation of complex material systems. I will briefly introduce the machine-learning-enabled energy predictors, and show their applications in complex perovskite materials and novel complex earth-abundant solar cell materials. I will demonstrate that the machine-learning-enabled models offer tens of thousand times computational speedup relative to first-principle calculations, and will also discuss the drawback of these models.