Kethan is a Research Associate in Autonomous Vehicle Modelling at the Transport Systems and Logistics Laboratory, Centre for Transport Studies at Imperial College London. He currently works on the DeepSafe project.
Kethan joined the Centre for Transport Studies in December 2023. Prior to this, he was an AI Engineer and Data Science Consultant for Capita. There he leveraged ML techniques, such as Natural Language Processing and Computer Vision, to build bespoke and tailored products for various use cases in the public sector. Some examples include working alongside the Food Standards Agency (FSA) and the Centre for Genomic Pathogen Surveillance (based out of the University of Oxford) to facilitate the build of an interoperable genomic system, developing models and software infrastructure to partially automate operational processes in TfL’s Road User Charging scheme, and was a Product Lead for an in-house MLOps platform to automate the end-to-end data science and machine learning lifecycle.
Kethan holds a first-class MPhys. degree in Condensed Matter Physics from the University of Kent, as well as an MSc. degree in Machine Learning from University College London (UCL).
Kethan’s MPhys. Condensed Matter Physics thesis work is published in Physical Review B, where he helped explicitly construct the Hamiltonians for certain 1-dimensional topological insulators. His MSc. thesis in Machine Learning analysed emergent phenomena in Elementary Cellular Automata (ECA) using ML techniques and a mathematical formalism of a phenomenological theory of consciousness (called IIT 3.0).
MSc. in Machine Learning, 2020
University College London (UCL)
Year Abroad (Condensed Matter Physics, General Relativity, Cosmology), 2017
University of California, Santa Barbara
MPhys. Physics with a Year Abroad, 2015
University of Kent, Canterbury (UKC)