Achieving ML Robustness by Leveraging Physics-based Constraints

Research Overview

Drs. Atul Prakash (Computer Science and Engineering) and Huei Peng (Mechanical Engineering) aim to improve the robustness of machine learning models by taking advantage of environmental context, particular laws of physics and semantic background information. This new approach to machine learning can lead to reduced training needs and more robust learning even with significant perturbations.

Research Impact

Research Team

Dr. Atul Prakash, Computer Science and Engineering Division, University of Michigan, Ann Arbor

Dr. Huei Peng, Department of Mechanical Engineering, University of Michigan, Ann Arbor