"Advancing Density Functional Theory: Formulations, Boundary Conditions, and Machine Learning"
Phanish Suryanarayana
Department of Civil and Environmental Engineering, Georgia Tech
Friday, Oct 30, 2026 
- Colloquium - 499 DSL Seminar Room
- 03:00 to 04:30 PM Eastern Time (US and Canada)
Abstract:
Over the past few decades, Kohn–Sham density functional theory (DFT) has become a cornerstone of materials and chemical sciences research by virtue of the predictive power and fundamental insights it provides. However, such calculations are computationally expensive and the boundary conditions imposed are often ill-suited to the system of interest. The speaker will discuss efforts to overcome these limitations across three thrusts: scalable formulations of DFT, novel boundary condition formalisms, and the use of machine-learning techniques. The speaker will also discuss the applications enabled by these developments, ranging from nanoscience and surface science to warm dense matter.
Speaker Biography:
Prof. Phanish Suryanarayana, from Georgia Tech (Department of Civil and Environmental Engineering), is a computational scientist working on multiscale modeling of materials and structures, with an emphasis on density functional theory and also on developing machine learning methods to accelerate these calculations.
