Research

Overview

My research focuses on machine learning, optimization, and their applications in environmental science.

Research Projects

• Reduced Order Modeling for Plume Dynamics
  

  Developing fast reduced order modelings for characterizing plume dynamics directly from video data.

• Joint SINDy
  

  Developing a new model learning architecture inspired by the widely used (two-step) Sparse Identification of Nonlinear Dynamics (SINDy) that learns a model in scenarios of extremely scarce or noisy data measurements.

Publications

• Publication 1: Ike Griss Salas, Megan R. Ebers, Jake Stevens-Haas, and J. Nathan Kutz, Course graining and reeduced oder models for plume dynamics, Journal/Conference, Year.

Contact

LinkedIn: linkedin.com/in/ike-griss-salas
GitHub: https://github.com/MalachiteWind