Shreshth Malik
Shreshth Malik
Department of Computer Science,
Parks Road 14/15,
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Biography
Shreshth is a DPhil student in the OATML group, supervised by Yarin Gal and Stephen Roberts, and is a member of the AIMS CDT. His main research interests are problems that limit ML systems to be taken out of the lab and used with confidence in the real world, motivated by applications in the sciences. This includes topics such as incorporating physical inductive biases into neural networks, data-efficient learning, and differentiable simulations. He was recently a PhD researcher on the NASA FDL-X program. He also is interested in mitigating short/long term AI risk, collaborating with the causal incentives working group. 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).