I am Shashank Pathak, a PhD student in the Department of Computing Science at the University of Alberta. My research interests span computer vision, applied deep learning for dynamic system modeling, inverse problems, genomics, and aspects of continual learning. My current work focuses on continuous image super-resolution using flow-based models, as well as approximating PC-MRI metrics in the ascending aorta to enable surrogate estimation of stroke volume. In parallel, I pursue independent research on continual learning for multi-species codon optimization, to adapt a single model to perform effective codon adaptation across diverse species. Outside of research, I am a sports enthusiast- particularly cricket, table tennis, badminton, and chess.
UAlbertaVISUAL
Video Image Signal Understanding and Learning Laboratory at University of Alberta