About

Vansh Sharma is a highly skilled Ph.D. student in Computational Sciences, with expertise in Physics-based Simulations, Bayesian Inference, and Statistical Learning. He is currently pursuing his Ph.D. at the University of Michigan, where he is focused on computational science, algorithms, and statistics. As a Graduate Student Research Assistant at the University of Michigan, Vansh has worked on several projects related to Chemical Reaction Models, Dynamic Species Reduction for Multi-Cycle Computational Fluid Dynamics (CFD) Simulations, and Helical Drive Tactical Genset. He has also developed GT-Power models for engines and fuel systems, as well as Electric Turbochargers and Miller Cycles. Vansh has a strong educational background, with a Bachelor's degree in Mechanical Engineering from Delhi Technological University and a Master's degree in Mechanical Engineering from the University of Michigan. He is currently pursuing his Ph.D. in Mechanical Engineering at the University of Michigan and is expected to complete it in 2025. In addition to his academic and professional experience, Vansh has also developed skills in Python programming and is a Research Scientist. He has 2.37 years of relevant experience and is passionate about optimizing high-dimensional models and uncertainty quantification of models. Overall, Vansh is a highly motivated and skilled Ph.D. student with a strong background in computational science, algorithms, and statistics. He is committed to developing innovative solutions to complex problems and is driven by a passion for research and learning.