(pronounced as vid-he)
Academic
Social
I am based between the new and the old Cambridge, in Massachussetts and the UK!
I am an Eric and Wendy Schmidt Center (EWSC) postdoctoral fellow at the Broad Institute of MIT & Harvard. I work with Prof. Caroline Uhler at MIT and EWSC.
My research interests are broadly in Bayesian non-parametric models like Gaussian Processes and probabilistic methodologies for machine learning.
I actively work in scientific applications of probabilistic machine learning to problems in contemporary sciences like computational biology, high energy physics and astronomy. I currently work on generative models for small molecules in the space of drug-discovery and the evaluation of foundational models for discovery pipelines in molecular machine learning and single-cell RNA seq data.
I completed my PhD at the University of Cambridge (UK) in 2023. I was based at the Cavendish Laboratory (Physics) and the Computational & Biological Learning Lab at the Dept. of Engineering. During my time in Cambridge I was a Turing Scholar and a member of Christ’s College. I was awarded a G-Research PhD prize in 2023 for my thesis and a Qualcomm Innovation Fellowship in 2020.
I was supervised by Prof. Carl Rasmussen and Prof. Neil Lawrence both at Cambridge. I also hold a MPhil in Scientific Computing with Distinction (Cambridge), MSc. in Applicable Mathematics with Distinction (LSE) and a BSc. in Mathematics with First Class Honors (Univesity of London, External).
Education
Core Interests
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Gaussian processes
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Hierarchical Probabilistic Models
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Kernel Design
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Generative Models
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Geometric interpretations
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Transformers
Industry: Prior to Cambridge I worked in algorithmic market making for global electronic FX markets at Credit Suisse and as a high frequency proprietary trader in pan-European equities at the (then) Chicago-based hedge fund, Citadel LLC between 2011 and 2015.