We are honored to have Professor Jing Ma from Nanjing University to give a lecture in Shenzhen Bay Laboratory.
Topic: Data-driven Sampling Method and the Modified Force Fields for Simulations of Conformational Changes
Abstract: In this talk, I will introduce the data-driven approach, named Data-Driven Accelerated (DA2) method, to increase the efficiency of the conventional molecular dynamics in sampling of the conformational transitions at atomic level with target-unspecified feature. Initialized by the normal mode analysis (NMA), the principle component analysis (PCA) was applied on-the-fly to reduce the redundant information. Such a scheme was also extended to search the possible transition paths between the two known target conformations. The electrostatics polarization models and variable force field models were also proposed to give more accurate predictions of physical properties of the complex systems.
Professor Jing Ma obtained her bachelor's and master's degrees from Nanjing University of Science and Technology in 1992 and 1995, and her Ph.D. degree in physical chemistry from Nanjing University in 1998. From 1998 to 2000, as a special researcher of the Japan Society for the Promotion of Science (JSPS), she did post-doctoral research at Gifu University, Japan. From 2000 to 2005, she was an associate professor of Nanjing University. Since July 2005, she has been a professor in the School of Chemistry and Chemical Engineering of Nanjing University. Since April 2006, she has served as a doctoral supervisor. Teacher Fund, won the National Outstanding Youth Fund in 2008, and won the Ninth China Young Women Scientist Award in 2012. Professor Jing Ma’s main research direction is the development of electronic structure theory and molecular simulation methods and their applications in functional materials. Her research interests include: theoretical design of conductive polymer materials; surface and interface stacking structure and chemical reactions; main group elements Chemical. During the period, more than 250 papers were published. The total number of citations of Web of Science papers has exceeded 8,200, and the H factor is 44.