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I am based between the new and the old Cambridge, in Massachussetts and the UK!  

vidrl@mit.edu 

vr308@cam.ac.uk

vrameshl@broadinstitute.org

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

 

  • Gaussian processes

 

  • Hierarchical Probabilistic Models

 

  • Kernel Design 

 

  • Generative Models 

 

  • Geometric interpretations

  • 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.

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