Course Information

The goal of physics-informed machine learning (PIML) is to build a model that uses real-world data and physical prior knowledge to improve performance on a set of tasks that involve a physical mechanism.  

The focus of this course is on reading and critiquing published research papers, and on doing a semester-long research project.

We will read and analyze the strengths and weaknesses of research papers on a variety of important topics pertaining to physics informed machine learning, and identify open research questions. See the schedule for a list of topics we will cover.

Through the course of the semester, you will also undertake a research project with a concrete objective, likely in teams of 2 students (depending on enrollment). While certainly not a requirement for the class, students should actively consider submitting a paper at the end of the course to a top-tier conference in Machine learning, or top journal in their own fields.

Class meets: Tu, Th 9:00AM - 10:15AM Amundson Hall 162