Davit Potoyan

Davit Potoyan is an Associate Professor in the Department of Chemistry at Iowa State University's College of Liberal Arts and Sciences, with courtesy faculty appointments in both the Biochemistry, Biophysics and Molecular Biology (BBMB) and Bioinformatics and Computational Biology (BCB) programs. His research group, CATBio (Computation, AI & Theory-Driven Biophysics), develops computational approaches to study biomolecular systems.

Professor Potoyan's research interests focus on computational biophysics, particularly using multi-scale computational tools rooted in statistical physics, machine learning, and data analytics to study biologically motivated problems. His group investigates the condensation of disordered proteins and nucleic acids, enzyme dynamics, chromatin organization, and epigenetic networks of stem cells. Current research is organized into four main directions: developing AI- and physics-based methods to predict allosteric communication in biomolecular assemblies; uncovering sequence-encoded dynamics in biomolecular condensates using multi-scale computational models; constructing mesoscopic and systems-level models to elucidate transcriptional and epigenetic regulation of chromatin; and advancing generative and explainable AI approaches for modeling and interpreting biomolecular dynamics.

Analysis of his recent publications (2024-2025) reveals a strong focus on biomolecular condensates, chromatin organization, and protein-RNA interactions. His work combines computational approaches with theoretical biophysics to address fundamental questions in phase separation, allosteric regulation, and nuclear organization. The research spans from atomistic simulations to mesoscale modeling, demonstrating an integrated approach to understanding biological phenomena across multiple spatial and temporal scales.

Professor Potoyan actively recruits postdoctoral researchers, PhD students, and undergraduate students with backgrounds in Physics, Chemistry, Engineering, Computer Science, or Applied Mathematics who have experience with scientific coding (C/C++/Python).