page updated in September 2022
Seungmoon Song

Assistant Professor
Mechanical and Industrial Engineering
Northeastern University
Boston, MA

Email: s.song at northeastern dot edu
CV




I am looking for Ph.D. students to join my lab. Email me if you are interested in pursuing a Ph.D. in the following topics.

1. Developing versatile gait assistive exoskeleton controllers through neuromechanical simulations
2. Modeling human locomotion control using deep reinforcement learning


I am an assistant professor in Mechancial and Industrial Engineering at Northeastern University. The goal of my lab is to better understand and model the motor control and biomechanics of human locomotion and to apply the obtained knowledge to rehabilitation engineering. We develop computational models and conduct human experiments to propose and evaluate control hypotheses. I envision our research to bring about simulation testbeds (which I call digital locomotor clones) for training protocols and assistive devices as well as intelligent motion controllers for assistive and humanoid robots.


Journal papers


Optimized hip-knee-ankle exoskeleton assistance reduces the metabolic cost of walking with worn loads
GM Bryan, PW Franks, S Song, R Reyes, MP O'Donovan, KN Gregorczyk & SH Collins
Journal of NeuroEngineering and Rehabilitation, 2021
[paper]

Optimized hip-knee-ankle exoskeleton assistance at a range of walking speeds
GM Bryan, PW Franks, S Song, AS Voloshina, R Reyes, MP O'Donovan, KN Gregorczyk & SH Collins
Journal of NeuroEngineering and Rehabilitation, 2021
[paper]

Deep reinforcement learning for modeling human locomotion in neuromechanical simulation
S Song, Ł Kidziński, XB Peng, C Ong, J Hicks, S Levine, CG Atkeson & SL Delp
Journal of NeuroEngineering and Rehabilitation, 2021
[paper] [video 2017] [video 2018] [video 2019]

Optimizing exoskeleton assistance for faster self-selected walking
S Song & SH Collins
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021
[paper] [video 1] [video 2] [video Stanford] [press]

Using force data to self-pace an instrumented treadmill and measure self-selected walking speed
S Song, H Choi & SH Collins
Journal of NeuroEngineering and Rehabilitation, 2020
[paper] [code] [video]

Predictive neuromechanical simulations indicate why walking performance declines with aging
S Song & H Geyer
The Journal of Physiology, 2018
[paper] [press]

Evaluation of a Neuromechanical Walking Control Model Using Disturbance Experiments
S Song & H Geyer
Frontiers in Computational Neuroscience, 2017
[paper] [video 1] [video 2]

A neural circuitry that emphasizes spinal feedback generates diverse behaviours of human locomotion
S Song & H Geyer
The Journal of Physiology, 2015
[paper] [video] [model] [journal cover]



Conference papers


Bayesian optimization using domain knowledge on the ATRIAS biped
A Rai, R Antonova, S Song, W Martin, H Geyer & CG Atkeson
IEEE ICRA, 2018
[paper] [video]

Towards a hierarchical neuromuscular control model with reflex-based spinal control - A study with a simple running model
S Song
International Symposium on Advanced Intelligent Systems, 2015
[paper] [video] [best presentation award]

Regulating speed in a neuromuscular human running model
S Song & Hartmut Geyer
IEEE Humanoids, 2015
[paper] [video]

Toward a virtual neuromuscular control for robust walking in bipedal robots
Z Batts, S Song & Hartmut Geyer
IEEE IROS, 2015
[paper] [video]

Development of a bipedal robot that walks like an animation character
S Song, J Kim & K Yamane
IEEE ICRA, 2015
[paper] [video] [talk] [press]

Integration of an adaptive swing control into a neuromuscular human walking model
S Song, R Desai & H Geyer
IEEE EMBC, 2013
[paper] [video]

Generalization of a muscle-reflex control model to 3D walking
S Song & H Geyer
IEEE EMBC, 2013
[paper]

The effect of foot compliance encoded in the windlass mechanism on the energetics of human walking
S Song, C LaMontagna, SH Collins & H Geyer
IEEE EMBC, 2013
[paper] [video] [project page]

Regulating speed and generating large speed transitions in a neuromuscular human walking model
S Song & H Geyer
IEEE ICRA, 2012
[paper] [video] [slides]

The energetic cost of adaptive feet in walking
S Song & H Geyer
IEEE ROBIO, 2011
[paper] [slides] [project page]

Development of an omnidirectional walking engine for full-sized lightweight humanoid robots
S Song, YJ Ryoo & DW Hong
ASME IDETC, 2011
[paper] [video1] [video2] [slides] [project page]

Linear-time encodable rate-compatible punctured LDPC codes with low error floors
S Song, D Hwang, S Seo & J Ha
IEEE VTC, 2008
[paper]



Patents

J Kim, K Yamane & S Song, Method for developing and controlling a robot to have movements match-ing an animation character, United States Patent 9427868, 2016. [link]

J Nam, J An, D Hwang, J Ha & S Song, Apparatus and method for encoding low density parity check code, Korean patent 10-0999272-00-00, 2010. [link]




Conference abstracts

Invited talks