marissalee@stanford.edu
Clark Center, Room S341
Bio
I combine statistical and biomechanical models to improve mobility in clinical populations. I am a member of the Mobilize Center and Stanford Data Science. In my non-working hours, you’ll catch me skiing, playing tennis, or (most often) eating.
Research Interests
Combining statistical and biomechanical models to improve mobility in clinical populations. Thesis projects aim to:
- Detect freezing of gait in individuals with Parkinson’s disease using wearable sensors and deep learning
- Understand the relationships between walking gait and bone health in children with pathological gait
- Identify patient-specific determinants of intervention success in patellofemoral instability, using novel 3D imaging measures and machine learning techniques
Education
M.S. in Mechanical Engineering, Stanford University, 2020
B.S. in Engineering, Harvey Mudd College, 2018
Honors and Awards
Stanford Data Science Scholar, 2022
Stanford Graduate Fellowship, 2018
Publications
Uhlrich SD*, Uchida TK*, Lee MR, & Delp SL. Ten steps to becoming a musculoskeletal simulation expert: A half-century of progress and outlook for the future. Journal of Biomechanics 154, 111623. (*co-first authors) Article
Lee MR, Hicks JL, Wren TAL, & Delp SL. Independently ambulatory children with spina bifida experience near-typical knee and ankle joint moments and forces during walking. Gait & Posture 99, 1-8. Article
O’Day J*, Lee M*, Seagers K*, Hoffman S, Jih-Schiff A, Kidzinski L, Delp S†, & Bronte-Stewart H.† Assessing inertial measurement unit locations for freezing of gait detection and patient preference. Journal of NeuroEngineering and Rehabilitation 19, 20. (*co-first authors, †co-last authors) Article