Welcome to the Raymond Lab
About
Data and data-driven decisions will be vital as we tackle the coming decade’s challenges. The Raymond Lab focuses on the need for a fundamental appreciation and skillset of data management and how we can leverage computational modeling to accelerate our modeling challenges.
Featured Research Projects
Pre-Training
Using simulated results to navigate deep learning to a point where the limited amount of real-world data can push the model to its optimal state.
Physics-based Loss Functions
Adding terms like conservation of energy, momentum, and other important laws into the optimization process to improve model generalizability and ensure realistic predictions.
Synthetic Data for Inverse Modeling
Some models that predict how a system will evolve from one point to another cannot be inverted to go backwards. Synthetic datasets from these numerical models can be used to train a deep learning model to let us invert these problems and discover the initial or boundary conditions.