Computational Modeling
High-fidelity modeling of reacting flows, spray combustion, turbulence, and multiphase phenomena.
Simulate.Learn.Optimize.
We develop physics-informed, data-driven models and optimization methods for complex engineering systems.
The aim of exact science is to reduce the problems of nature to the determination of quantities by operations with numbers.
James Clerk Maxwell
Research Interests
Scientific Machine Learning
Physics-informed and data-driven models for prediction, reduction, and uncertainty quantification.
Design Optimization
Gradient-based and surrogate-assisted optimization for energy systems and processes.
Funding Sources
