"Toward Next-Generation Quantum Chemistry: Scalable and Accurate Frameworks Based on Grassmannians, Fragmentation, and Quantum-Informed Machine Learning.”

Prof. Ka Un Lao

Virginia Commonwealth University, Dept of Chemistry

Co-Hosts: Dr. Xueyu Song and Dr. Theresa Windus

Bio: Dr. Ka Un Lao is a current Associate Professor at Virginia Commonwealth University and focuses on developing and applying new electronic structure models and algorithms based on quantum mechanics, combining concepts and techniques from chemistry, physics, mathematics, and computer science, to study molecules, clusters, and condensed phase systems, ranging from chemistry to biochemistry and materials science. 

He was a postdoc at Cornell University in Ithaca, New York, earned his Ph.D., at The Ohio State University as well as his M.S. and B.S., at National Tsing Hua University in Taiwan. 

One particular area of emphasis is the accurate and efficient calculation of intermolecular interactions, which is a challenging problem for electronic structure theory. His research goal is to develop fast and accurate approaches for gaining a fundamental understanding of the factors governing the drug binding and molecular materials packing in order to provide a basis for the development of new drug binding molecules and functionalized molecular materials. Furthermore, adapting the methodology we are going to develop to the rapid evolution of machine-learning techniques offers a unique opportunity to generate new noncovalent molecular electronics and drug molecules through large-scale computational screening and design since the combination of different strategies to functionalize molecules is seemingly infinite. His group primarily works with a quantum chemistry software program called Q-Chem, to which we contribute new methods and algorithms.