Shashank Subramanian is a NESAP for learning postdoctoral fellow with research interests in the intersection of high-performance scientific computing, deep learning, and physical sciences. His current research involves developing large-scale neural networks for high resolution, data-driven weather prediction and on algorithmic developments to understand and improve physics-informed neural networks.
Prior to joining NERSC, Shashank received his PhD in Computational Sciences and Applied Mathematics from UT Austin in 2021. His doctoral research focused on integrating mathematical models of cancer growth with patient-specific imaging data using efficient parallel algorithms, optimization methods, and high-performance computing software to improve personalized medicine. Shashank received his Bachelors in Aerospace Engineering from the Indian Institute of
Technology Madras in 2016.