Seungmoon Song

Assistant Professor,  Mechanical and Industrial Engineering

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  • 259 SN

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Research Focus

Modeling the neuromechanics of human movement and applying it to assistive devices and rehabilitation treatment

About

Seungmoon Song will join Northeastern University in January 2022 as an assistant professor in Mechanical & Industrial Engineering. His research focuses on modeling the neuromechanics of human movement and applying it to rehabilitation and robotics. He is currently a postdoctoral researcher in the Mechanical Engineering Department of Stanford University and a recipient of an NIH K99 award working on improving human walking performance with exoskeleton assistance using human-in-the-loop optimization. He is also the lead organizer of the NeurIPS: Learn to Move competition. During his Ph.D. at the Robotics Institute of Carnegie Mellon University, he proposed a reflex-based control model that could explain various aspects of human locomotion including diverse locomotion behaviors of healthy adults, responses to unexpected disturbances, and performance degradation in aging. He developed walking controllers for humanoid robots as a Master’s student at Virginia Tech and received a Bachelor’s degree at ICU (now merged into KAIST) in Korea.

Education

PhD, Carnegie Mellon University, 2017

Research Overview

Modeling the neuromechanics of human movement and applying it to assistive devices and rehabilitation treatment

Selected Research Projects

  • Simulation Framework to Develop Ankle Exoskeleton Gait Assistance for Older Adults
    • – PI, NIH

Selected Publications

  • S Song, Ł Kidziński, XB Peng, C Ong, J Hicks, S Levine, CG Atkeson, & SL Delp, Deep reinforcement learning for modeling human locomotion in neuromechanical simulation,Journal of NeuroEngineering and Rehabilitation, 2021.
  • S Song & SH Collins, “Optimizing exoskeleton assistance for faster selfselected walking speed, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021.
  • S Song, H Choi, SH Collins, “Using force data to self-pace an instrumented treadmill and measure self-selected walking speed,” Journal of NeuroEngineering and Rehabilitation, 2020.
  • S Song and H Geyer, “Predictive neuromechanical simulations indicate why walking performance declines with aging” The Journal of Physiology, 2018.
  • S Song and H Geyer, “Evaluation of a neuromechanical walking control model using disturbance experiments,” Frontiers in Computational Neuroscience, 2017.
  • S Song and H Geyer, “A neural circuitry that emphasizes spinal feedback generates diverse behaviours of human locomotion,” The Journal of Physiology, 2015.
Seungmoon Song

Faculty

Jan 03, 2022

New Faculty Spotlight: Seungmoon Song

Seungmoon Song joins the Mechanical and Industrial Engineering department in January 2022 as an Assistant Professor.

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