Peng Liu is a Professor of Chemistry at the University of Pittsburgh. He received his B.S. degree from Peking University in 2003 and M.Sc. degree from the University of Guelph in 2006. He completed his Ph.D. study and performed postdoctoral research at UCLA. He joined the University of Pittsburgh as an Assistant Professor in 2014 and was promoted to Associate Professor in 2019 and Full Professor in 2022. Since 2015 he has been an adjunct faculty member in the Department of Chemical and Petroleum Engineering at the University of Pittsburgh. He is currently a member of the Pittsburgh Quantum Institute and the Computational Modeling and Simulation program at Pitt. He has mentored 26 graduate students, 5 postdocs, and 27 undergraduate and high school students. His research accomplishments have been recognized by a number of awards, including the NSF CAREER award (2017), the Journal of Physical Organic Chemistry Award for Early Excellence (2018), the NIH Maximizing Investigators' Research Award (2018), Innovation in Education Award (2020), and Chancellor’s Distinguished Research Award (2020). He has published over 200 manuscripts. Prof. Liu's research focuses on addressing the grand challenges in computational studies of catalytic organic reactions. He introduced transformative computational approaches to the organic chemistry community to study catalytic reaction mechanisms and catalyst effects on reactivity and selectivity. He has significantly expanded the capabilities of utilizing computational studies to provide chemically meaningful insights into complex mechanistic scenarios. Prof. Liu's research has led to new understanding of several important, but often overlooked factors in catalysis, including catalyst–substrate non-covalent interactions, catalyst flexibility, substrate ring strain, and solvent effects.Prof. Liu have employed next-generation computational tools in various catalytic systems, including transition metal catalysis, polymerization, glycosylation, photoredox catalysis, and biocatalysis with engineered metalloenzymes. These catalytic reactions enabled selective synthesis of functionalized molecules via novel bond formation strategies. The mechanistic insights from Prof. Liu's computational studies provided the theoretical foundation of new experimental methodology development and practical catalyst design principles to accelerate experimental discovery.