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Challenger Mishra

Postdoc (2018—2020)

Challenger is a theoretical physicist working on the long-standing problem of quantising gravity. Recently, he started to undertake work in Theoretical Machine Learning, in order to exploit its tools to understand String Theory as a problem in big data. As a Rhodes Scholar he has pursued his passion in understanding fundamental physical processes by undertaking doctoral work in String Theory at the Rudolf Peierls Centre for Theoretical Physics, University of Oxford. During his recently completed thesis, he worked on understanding various aspects of complex geometries that feature in String Theory, using the tools of differential and algebraic-geometry. Prior to this, Challenger completed his undergraduate work in Physics from the Indian Institute of Science Education and Research, Kolkata. During his undergraduate years, he worked on a NASA-sponsored project applying stochastic optimisation techniques to analyse data from the proposed gravitaional wave detector, LISA. When he isn’t tied up in stringy or machine learning affairs, he likes to show off his constantly diminishing skills in table tennis. After OATML, Challenger was appointed as an Accelerate Science Research Fellow at the University of Cambridge.

Are you looking to do a PhD in machine learning? Did you do a PhD in another field and want to do a postdoc in machine learning? Would you like to visit the group?

How to apply


We are located at
Department of Computer Science, University of Oxford
Wolfson Building
Parks Road
Twitter: @OATML_Oxford
Github: OATML