Peetak is a final year Ph.D. candidate at the University of Massachusetts Amherst. His research interests are at the intersection of machine learning and computational physics. Peetak is a co-founder of $400,000 data-driven industry-funded consortium, called ICEnet which leverages machine learning to accelerate scientific computing for engine design and research. Peeetak completed part of his thesis dissertation at the Los Alamos National Laboratory and spent summer 2020 working with TOTAL S.A, on developing high-performance machine learning tools.