Shashank Subramanian

Shashank Subramanian is a Research Engineer at Berkeley Lab since July 2021, focusing on deep learning research in high-performance computing and artificial intelligence for physical sciences. Prior experience includes a Postdoctoral Researcher role, where Shashank worked on large-scale neural network surrogate models for medium-range weather forecasting and algorithmic developments for enhancing the robustness of physics-informed neural networks. At The University of Texas at Austin, Shashank served as a Graduate Research Assistant, developing parallel algorithms and scalable software for cancer growth models and contributing to nonconvex PDE-constrained optimization problems. Additional experience includes a Research Intern position at Berkeley Artificial Intelligence Research, concentrating on convolutional neural networks for medical imaging. Shashank holds a PhD and MS in Computational Science and Applied Mathematics from The University of Texas at Austin and a dual degree (BTech + MTech) in Aerospace Engineering from the Indian Institute of Technology, Madras.