Prof Richard Wong

Richard Ming Wah Wong is one of the three Co-Directors of the Applied Materials-NUS Corporate Lab. Since 2015, he also served as the Head of Department of Chemistry at NUS. Richard received his PhD degree from the Australian National University in 1989. Subsequently, he held postdoctoral positions at IBM Kingston and Yale Unversity. He was awarded with a prestigious australian Research Felloship at University Queensland before he joined National University of Singapore in 1997. He rose through the ranks as senior lecturer, associate professor and full professor. Currently, he is also a senior member of the NUS Graduate School of Integrative Sciences & Engineering (NGS). 

Richard has published about 200 scientific publications, which received over 9400 citations with an H-index of 43. He was a recipient of the Outstanding Researcher Award in NUS in 2010 and the Fukui Award in 2018 for his outstanding research in computational chemistry in the Asia-Pacific region. He serves on the editorial advisory boards of Advance Theory & Simulation, Journal of Analytical & Pyrolysis, Asian Journal of Organic Chemistry and Australian Journal of Chemistry. His research interests include application of computational quantum chemistry and molecular dynamics simulations to a range of chemical, biochemical and materials problems, include organic reaction mechanisms, reactive intermediates, catalysis, supramolecular chemistry, materials design, chemical sensors, weak intermolecular interactions, computer aided drug design, cheminformatics and machine learning. His current research focuses on application of computational methods in the discovery and development of novel functional materials, which involves (1) structure predictions based on first principles (density functional theory) methods; (2) applying big data analytics and machine learning techniques on computationally derived data to make predictions of materials properties and suggest new materials; and (3) high throughout computation to screen experimentally determined crystal structures, stored in databases, for interesting or optimal properties.