Development of Computational Approaches for Molecular Property Predictions
ECE 595 Seminar Series
October 31, 2025
11:00 AM - 12:00 PM
Location
online only (email department for link and passcode)
Calendar
Download iCal FileDevelopment of Computational Approaches for Molecular Property Predictions
Presenter: Viki Kumar Prasad, University of Calgary
Abstract: The utility of computer modeling as a predictive and explicative tool, or complementary to experiments, continues to help advance chemistry. Computational chemists rely on quantum mechanical (QM) methods to understand the behavior of electrons in atoms and molecules and predict their structure and properties. However, the computational power required by highly accurate QM methods scales steeply with the system size, limiting their applicability. My research is centered on developing new computational tools that enable reduced resource use associated with molecular modeling while attaining high accuracy in chemical predictions. In this talk, I will present the development of atom-centered potentials using a machine learning algorithm (LASSO regression) that mitigates the shortcomings of Hartree–Fock and density functional theory methods, particularly when used with small basis sets (J. Chem. Theory Comput. 2022, 18, 2913–2930; J. Chem. Theory Comput. 2022, 18, 2208–2232). Next, I will discuss a data-driven approach utilizing atom-centered potentials to facilitate the development of a supervised deep-learning model capable of predicting a property central to chemistry – bond dissociation enthalpies – with high accuracy and at a computational cost significantly lower than QM methods (Mach. Learn.: Sci. Technol. 2024, 5, 015035). Lastly, I will present some recent and current results where we applied quantum computing techniques to understand the effectiveness and practical utility of this emerging technology for molecular property predictions (Phys. Chem. Chem. Phys. 2024, 26, 4071–4082; https://arxiv.org/abs/2507.08183). This talk will highlight various computational approaches with the potential to accelerate high-throughput modeling of molecular systems for those interested in structure-function relationships, a priori structure determination, and in silico design and discovery of new molecules.
Speaker bio: Viki Kumar Prasad is an assistant professor in the department of chemistry at University of Calgary. At the University of Calgary, he also serves as a faculty member of the Institute of Quantum Science and Technology and the Centre for Molecular Simulation, as well as a Quantum City Fellow. Before joining University of Calgary, Prasad did his postdoctoral research at the University of Toronto, a PhD in computational chemistry from the University of British Columbia, and a MS in chemistry from the Indian Institute of Technology Kharagpur. He was awarded a postdoctoral fellowship through the Data Sciences Institute at the University of Toronto, the Chemical Computing Group Excellence Award by the American Chemical Society’s Division of Computers in Chemistry, and best presenter at the Congress of World Association of Theoretical and Computational Chemists. Prasad’s work has been recognized through invitation to the Canadian Society for Chemistry’s 2025 Organic and Bioorganic Young Investigator’s Workshop and selection for the 2025 International Forum on Radical Interdisciplinarity co-hosted by the Canadian Institute For Advanced Research and Swiss National Science Foundation.
Faculty Host: Zizwe Chase, chase8@uic.edu
Date posted
Oct 29, 2025
Date updated
Nov 20, 2025