Summary
Eugen Hruška is an Assistant Professor and computational pharmaceutical scientist with 11 years of experience developing high-throughput atomistic simulations and explainable machine learning models for drug interactions. His work spans academic appointments at Charles University, postdoctoral research at Emory where he performed DFT-accurate explicit solvation simulations, and a PhD from Rice focused on scalable adaptive sampling for protein folding. He combines physics-rooted modeling, biochemistry background, and software-enabled automation to push simulation accuracy and throughput while emphasizing interpretability. Notably, he built open and scalable adaptive sampling tools that enabled deep learning-driven exploration of protein dynamics—bridging methodological advances with practical workflows in drug discovery.
10 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at Rice University
Bachelor's degree, Biochemistry, Bachelor's degree, Biochemistry at University of Regensburg
Bachelor of Science, Technical Physics, Bachelor of Science, Technical Physics at Technische Universität Ilmenau
German, English, Slovak