Meghan Huber is an assistant professor in the Department of Mechanical and Industrial Engineering at UMass Amherst and the principal investigator of the Human Robot Systems Laboratory. The mission of the lab is to (1) improve human-robot physical interaction using principles from human neuromotor control and perception and (2) advance how humans and robots learn to guide the physical interactive behavior of one another.

Her prior research focused on assessing and enhancing complex motor skill learning using virtual environments. She also developed multiple virtual rehabilitation systems for in-home use and worked on teams developing virtual training simulations for medical and military purposes.

Before joining UMass Amherst, she was a postdoctoral research associate in the Department of Mechanical Engineering at the Massachusetts Institute of Technology and a member of the Newman Laboratory under the direction of Professor Neville Hogan from 2016-2020. She received her Ph.D. in Bioengineering from Northeastern University in 2016 under the advisement of Prof. Dagmar Sternad, her M.S. degree in Biomedical Engineering from The University of Texas at Dallas in 2011, and her B.S. degree in Biomedical Engineering from Rutgers University in 2009. During her doctoral training, she was also a Visiting Junior Scientist in the Autonomous Motion Department at the Max Planck Institute for Intelligent Systems in Tübingen, Germany in 2014.

Recent News

Paper accepted to IROS 2018
Jongwoo Lee, Meghan Huber, Dagmar Sternad, and Neville Hogan will present "Robot Controllers Compatible with Human Beam Balancing Behavior" at IROS 2018.
1st Place Technical Design Award at MIT AT Hackathon
Danielle Feerst, James Hermus, Jongwoo Lee, David Mercado, and Meghan Huber won the first place technical design award at the MIT Assistive Technologies Hackathon for their zipper assist project.
Paper Published in PLoS Computational Biology
"Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise" by Zhaoran Zhang, Dena Guo, Meghan Huber, Se-woong Park, and Dagmar Sternad is now available in PLoS Computational Biology.