Research Interests

Large Language Models, Physics-informed Machine Learning, Computational Mechanics, Particle-based Simulation Methods

Education

• PhD, Massachusetts Institute of Technology, 2020
• MEng, Monash University, Australia, 2015
• BEng Monash University, Australia, 2012

Selected Publications

• Raymond SJ, Collins DJ, O’Rorke R, Tayebi M, Ai Y, Williams J. "A deep learning approach for designed diffraction-based acoustic patterning in microchannels ." Scientific Reports. 10(1): 8745.
• Bell SM, Raymond SJ, Yin H, Jiao W, Goll DS, Ciais P, Olivetti E, et al. "Quantifying the recarbonization of post-agricultural landscapes." Nature Communications. 14(1): 2139.
• Raymond SJ, Cecchi NJ, Alizadeh HV, Callan AA, Rice E, Liu Y, Zhou Z, et al. "Physics-informed machine learning improves detection of head impacts." Annals of Biomedical Engineering. 50(11): 1534-1545.
• Zhan X, Liu Y, Raymond SJ, Alizadeh HV, Domel AG, Gevaert O, et al. "Rapid estimation of entire brain strain using deep learning models." IEEE Transactions on Biomedical Engineering. 68(11): 3424-3434.
• Raymond SJ, Baker S, Liu Y, Bustamante MJ, Ley B, Horzewski MJ, et al. "A low-cost, highly functional, emergency use ventilator for the COVID-19 crisis." Plos One. 17(3), e0266173.
• Raymond SJ, Jones B, Williams JR. "A strategy to couple the material point method (MPM) and smoothed particle hydrodynamics (SPH) computational techniques." Computational Particle Mechanics. 5: 49-58.

Courses

• ENGS 15.08: AI Demystified: A Roadmap to Understand Evolving Technologies