Materials research from the perspective of computing: data, model, and more
- Ziheng Lu | Microsoft Research Asia
The way people search for a new material is undergoing a transition from “experimental trial and error” to “rational design”. While the current computational screening scheme based on existing databases has guided the synthesis of a number of key materials, the intrinsic limitation on chemical and structural space of the databases gradually impedes the further discovery of novel materials with desired functionality. This talk will briefly cover the current research paradigms, commonly used tools, and challenges in computational materials science. On that basis, the effort at Microsoft Research will be introduced, including Graphormer (a Transformer-based molecular modeling foundation model), Local Similarity kernel Optimization (LOSIKO, a data-driven atomic structure optimizer for unlabeled data), MoLeR (a graph-based model for molecule generation), and KD-DTI (a database for literature mining). Future perspectives will be discussed in the end.
Speaker Details
Ziheng is a Senior Researcher at Microsoft Research – Asia. He works at the intersection of materials science and machine learning. His current research focuses on computational and experimental design of new materials and their applications in downstream areas. His interest also falls into the general scope of ‘AI for science’. Prior to joining MSR, Ziheng earned his Ph.D. from the Hong Kong University of Science and Technology in 2018. Afterwards, he worked at various universities/research institutes including Yale, Chinese Academy of Sciences, the UK’s Faraday Institution, and University of Cambridge. He published over 50 peer-reviewed articles in Chem. Rev., Nat. Mater., Angew. Chem. Int. Ed., Adv. Energy Mater., Energy Storage Mater., Nano Energy, Chem. Mater., and J. Mater. Chem. A. He also serves as the associate editor for Frontiers in Energy Research, and guest editor for Materials Reports: Energy.
