Erik Thiede

Erik Thiede is an Assistant Professor in the Department of Chemistry and Chemical Biology at Cornell University. His research focuses on developing computational tools to understand protein motion and function by integrating machine learning with molecular simulation. He is particularly interested in combining simulation with experimental techniques such as cryogenic-sample electron microscopy and developing algorithms for finding allosteric drug candidates. Thiede's work aims to advance our understanding of protein dynamics at the atomic level, with potential applications in medical breakthroughs and technological innovation.

Erik Thiede is an Assistant Professor of Chemistry and Chemical Biology at Cornell University, specializing in the computational modeling and analysis of molecular systems. His research focuses on developing advanced methods for representing and analyzing molecules, including models of molecules, images of molecules, and models of images of molecules. Thiede's work integrates machine learning, statistical mechanics, and computational chemistry to study dynamic processes such as protein dynamics, conformational heterogeneity, and cryo-electron microscopy data analysis. His research bridges theoretical and experimental approaches to uncover the underlying mechanisms of molecular behavior and functional insights.