About me

My name is Michael and I am a second year Ph.D. student at the University of Colorado, Boulder working under Prof. Jed Brown. Prior to beginning my Ph.D. I worked as a Data Scientist in industry for several years where I had the opportunity to work on a range of problems across the healthcare, financial services, and public sectors.

My research interests are broadly in machine learning and optimization. I enjoy investigating ways to learn from new types of data or developing algorithms that are especially data efficient for certain classes of problems. Right now, I’m especially interested in ML for physics-driven systems where we have prior knowledge of system behavior in the form of PDEs, invariances, or conservation laws.

Outside of work, I do a lot of climbing, running, and reading.


  • 2021/9/28 - The updated version of our earlier workshop paper, now titled, “Learning to Assimilate in Chaotic Dynamical Systems” was accepted to NeurIPS 2021.
  • 2020/11/03 - Our paper on “Using Differentiable Physics for Self-supervised Assimilation of Chaotic Dynamical Systems” was accepted to the Workshop on Differentiable Vision, Graphics, and Physics at NeurIPS 2020.
  • 2020/02/27 - Presented on “Data Science in the Healthcare Industry” at CSU’s Data Science Seminar.