Shreshth is a DPhil student in the OATML group, supervised by Yarin Gal and Steve Roberts, and is a member of the AIMS CDT. His main research interests include improving the robustness of deep learning, causality, and AI safety/ethics, in order to enable more reliable applications of machine learning in the real world. He also enjoys applying machine learning methods to solve problems in the sciences. Previously, he has worked on understanding the challenges of using deep active learning in practice with Humanloop and David Barber, and predicting the outcomes of material syntheses with Alpha Lee. He holds Master’s degrees in Machine Learning (UCL) and Physical Natural Sciences (University of Cambridge).
Publications while at OATML • News items mentioning Shreshth Malik • Reproducibility and Code • Blog Posts