Nicholas Wimer is a part of the High-Performance Algorithms and Complex Fluids Group within the Computational Science Center. He focuses on developing advanced fuel injection strategies for compression ignition engines using various machine learning techniques like reinforcement learning. 

Research Interests

Computational fluid dynamics

Reacting fluid flows (combustion)

Internal combustion engines

Machine learning techniques

Education

Ph.D., Mechanical Engineering, University of Colorado

M.S., Mechanical Engineering, University of Colorado

B.E., Engineering, Dartmouth College

B.A., Engineering Physics/Applied Physics, Dartmouth College

Featured Work

Simulations of Advanced Compression Ignition Strategies Using Direct Numerical Simulation and Lower Order Methods

Machine Learning Techniques for Adaptive Control Strategies and Model Development