
Shruti Mishra
I am a multidisciplinary scientist with a focus on reinforcement learning and continuum mechanics. I worked as a Research Scientist in reinforcement learning at Sony AI, developing methods for PlayStation games and open-source domains. I earned my PhD in Applied Mathematics from Harvard University, where I worked on problems in continuum mechanics, computation and machine learning. I have spent some time learning and doing research at DeepMind, on reinforcement learning in continuous control environments, and at Mila, on the use of deep learning to forecast natural convection.
I am open to research opportunities for the academic year 2026 and beyond. I welcome enquiries from institutions where my experience and interests might be a good match.
Education
PhD, Applied Mathematics, Harvard University (2021) SM, Applied Mathematics, Harvard University (2017) MEng, Mechanical Engineering, Imperial College London (2014)
Publications
S. Mishra, M. Chang, V. Spandan, S.M. Rubinstein
Reinforcement Learning Conference, Finding the Frame workshop (2025)
[article]
[poster]
S. Mishra, A. Anand, J. Hoffmann, N. Heess, M. Riedmiller, A. Abdolmaleki, D.
Precup
Conference on Robot Learning, LocoLearn workshop (2024) [article]
[poster]
S. Mishra, S.M. Rubinstein, C.H. Rycroft
Journal of Fluid Mechanics (2022) [article] [code]
A. Abdolmaleki, S.H. Huang, G. Vezzani, B. Shahriari, J.T. Springenberg, S. Mishra,
D. Tirumala, A. Byravan, K. Bousmalis, A. György, C. Szepesvari, R. Hadsell, N.
Heess, M. Riedmiller (2021)
[article]
S. Mishra, W.M. van Rees, L. Mahadevan
Journal of the Royal Society Interface (2020) [article]
S. Mishra, A. Abdolmaleki, A. Guez, P. Trochim, D. Precup
Neural Information Processing Systems, NewInML workshop (2019) [article]
J. Hoffmann, Y. Bar-Sinai, L.M. Lee, J. Andrejevic, S. Mishra, S.M. Rubinstein,
C.H. Rycroft
Science Advances (2019)
[article]
[code]
S. Mishra, M. Aslaninejad, P. Savage, P.A. Posocco, J.K. Pozimski, A.P.
Letchford
Proceedings of the Particle Accelerator Conference (2013)
[article]
Professional Activities
Reviewing
Conference on Neural Information Processing Systems
Physical Review Letters
Reinforcement Learning Conference
AAAI Conference on Artificial Intelligence, workshops
International Conference on Machine Learning, workshops
Organising
RL Social at ICML 2021
Workshop at NeurIPS 2020, NewInML
Teaching and Mentoring
Teaching Assistant, Imperial College: ME1 Mathematics
Alumni Mentor, Imperial College
Panels
Imperial offer holders panel, 2022
Awards
G-Research Grant
for students and postdocs in quantitative fields (2021)
Summer Research Grant, Harvard University (2021)
Best Oral Presentation Award,
NewInML workshop, NeurIPS conference (2019)
Young Scientist
Travel Award,
Harvard Brain Initiative (2019)
Certificate of Distinction in
Teaching,
Harvard University (2019, 2017)
Bramwell
Medal,
Imperial College (2014)
Henry
Ford II Scholar Award in Mechanical Engineering,
Imperial College (2014)
Santander Final Year Scholarship, Imperial College (2013)
Frank
Turner Wilson Prize, Imperial College (2013, 2011)
Sir
Bruce White Laboratory Prize in Mechanical Engineering,
Imperial College (2012)
Faculty of Engineering Dean's List, Imperial College (2014, 2013, 2012, 2011)
Gold Prize and Best in school, UK Maths Challenge (2010)
News
Sep 2025: Starting an
Encode Fellowship
at
DAMTP, Cambridge,
working on AI for multiscale flows.
Aug 2025: Presented
"A perspective on fluid mechanical environments for challenges in reinforcement learning"
at the
Finding the Frame workshop
at
RLC.
July 2025: Volunteered at
EEML.
June 2025: Co-organised a
workshop at RLDM.
May 2025: Invited talk at the AI4Good Lab
on Applications of reinforcement learning in locomotion.