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Shreshth Malik
PhD, started 2021
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
Publications while at OATML:
Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels
Automated planetary transit detection has become vital to prioritize candidates for expert analysis given the scale of modern telescopic surveys. While current methods for short-period exoplanet detection work effectively due to periodicity in the light curves, there lacks a robust approach for detecting single-transit events. However, volunteer-labelled transits recently collected by the Planet Hunters TESS (PHT) project now provide an unprecedented opportunity to investigate a data-driven approach to long-period exoplanet detection. In this work, we train a 1-D convolutional neural network to classify planetary transits using PHT volunteer scores as training data. We find using volunteer scores significantly improves performance over synthetic data, and enables the recovery of known planets at a precision and rate matching that of the volunteers. Importantly, the model also recovers transits found by volunteers but missed by current automated methods.
Shreshth Malik, Nora L. Eisner, Chris J. Lintott, Yarin Gal
Machine Learning and the Physical Sciences workshop, NeurIPS 2022
[paper]
Blog Posts
OATML Conference papers at NeurIPS 2022
OATML group members and collaborators are proud to present 8 papers at NeurIPS 2022 main conference, and 11 workshop papers. …
Full post...Yarin Gal, Freddie Kalaitzis, Shreshth Malik, Lorenz Kuhn, Gunshi Gupta, Jannik Kossen, Pascal Notin, Andrew Jesson, Panagiotis Tigas, Tim G. J. Rudner, Sebastian Farquhar, Ilia Shumailov, 25 Nov 2022