About

Megan R. Ebers is a postdoctoral scholar in applied mathematics with the NSF AI Institute in Dynamic Systems at the University of Washington. In her PhD research, she developed and applied machine learning methods for dynamical systems to understand and enable human mobility. Her postdoctoral research focuses on data-driven and reduced-order methods for complex systems, so as to continue her work in human-centered research challenges and extend her research to a broader set of technical challenges, including turbulent flow modeling, natural disaster monitoring, and personalized health monitoring.

She was advised by Dr. Kat M Steele (who combines engineering, medicine, and accessible design to understand and enable human mobility) and Dr. J Nathan Kutz (who researches numerical methods for modeling complex dynamical systems). She was supported by the NSF Graduate Research Fellowship Program and the NSF AI Institute in Dynamic Systems.

When she’s not neck-deep in code, you’ll find her in the mountains hiking, climbing, or snowboarding.