Research Interests

Use of statistical learning tools to improve cerebral palsy treatment outcomes; building and testing of lower extremity musculoskeletal models

Degrees

M.S. Mechanical Engineering, Stanford University, 2013
B.S. Mathematics, Stanford University, 2010

Honors and Awards

Centennial Teaching Assistant Award, Stanford University, 2014

Representative Publications

Rajagopal, A., Kidziński, Ł., McGlaughlin, A.S., Hicks, J.L., Delp, S.L., Schwartz, M.H. Estimating the effect size of surgery to improve walking in children with cerebral palsy from retrospective observational clinical data. Scientific Reports, 2018.

Halilaj, E., Rajagopal, A., Fiterau, M., Hicks, J.L., Hastie, T.J., Delp, S.L. Machine Learning in Human Movement Biomechanics: Best Practices, Common Pitfalls, and New Opportunities. Journal of Biomechanics, Vol. 81, 2018.

Rajagopal, A., Dembia, C.L., DeMers, M.S., Delp, D.D., Hicks, J.L., Delp, S.L. Full body musculoskeletal model for muscle-driven simulation of human gait. IEEE Transactions on Biomedical Engineering, Vol. 63 (9), 2016.

Hicks, J.L., Uchida, T.K., Seth, A., Rajagopal, A., Delp, S.L. Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement. ASME Journal of Biomechanical Engineering 137(2):020905, 2015.