报告人：Pavlo O. Dral副教授（厦门大学化学化工学院）
I will give an introduction to how machine learning (ML) can be used to assist quantum chemical research in a variety of ways and show examples from our research. The latter will include: the Δ-learning approach, correcting the semiempirical quantum chemical Hamiltonian with ML, very accurate ML potential energy surfaces, and ML nonadiabatic excited-state dynamics
Pavlo Dral is an Associate Professor at Xiamen University from 2019. He won gold medal in the 36th International Chemistry Olympiad in Germany in 2004. Pavlo Dral received two M.Sc. degrees in 2010: one from University Erlangen-Nuremberg (Germany) in molecular nanoscience and another from the National Technical University of Ukraine “KPI” in chemical technology and engineering of organic compounds. He obtained his PhD in University Erlangen-Nuremberg with Prof. Timothy Clark in 2013 followed by post-doctoral stay with Prof. Walter Thiel in Max-Planck-Institute for Coal Research until 2019. His research area is practical computational chemistry performed with quantum chemical andmachine learning methods. Pavlo Dral published 31 peer-reviewed articles cited over 1100 times and his h-index is 16.