Vidhi Lalchand
Postdoctoral Fellowship at Broad Institute of MIT and Harvard
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolVidhi Lalchand is a machine learning researcher with nine years of experience specializing in probabilistic generative models and Gaussian processes, currently pursuing a postdoctoral fellowship at the Broad Institute and working with Prof. Caroline Uhler at MIT on computational generative drug discovery. Trained at Cambridge (PhD with Carl Rasmussen) and previously a Turing Scholar, she blends deep theoretical work in Bayesian nonparametrics with applied projects in therapeutic discovery and single-cell RNA-seq analysis. Her PhD thesis earned a G-Research prize and she was a Qualcomm Innovation Fellowship winner, reflecting a track record of high-impact academic recognition. Vidhi has industry experience translating models to practice—from fractional roles in deep generative chemical design at Sixfold Bioscience to quantitative roles in finance at Citadel and Credit Suisse—giving her a rare mix of rigor and product focus. She frequently bridges high-performance computing and probabilistic methodology to tackle real-world biomedical problems, and often brings kernel-method insights into generative model design. Based in Cambridge, MA, she combines academic depth with hands-on model deployment in drug discovery pipelines.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Machine Learning, Doctor of Philosophy (Ph.D.), Machine Learning at University of CambridgeMaster of Science (M.Sc.), Applicable Mathematics, Distinction, Master of Science (M.Sc.), Applicable Mathematics, Distinction at London School of Economics and Political Science
Github Skills (44)
bayesian-statistics10
variational-inference10
probabilistic-programming10
python10
statistics10
statistical-inference10
mcmc10
bayesian10
probabilistic10
probabilistic-models10
gaussian10
bayesian-inference10
modeling10
data-science9
gaussian-processes9
Programming languages (4)
Github contributions (5)
vr308/Generalised-Gaussian-Processes
Mar 2020 - Aug 2022
Contributions:72 commits, 65 pushes, 1 branch in 2 years 4 months
vr308/GPLVM
Dec 2020 - Jun 2021
Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch
Contributions:26 commits, 23 pushes, 3 branches in 6 months
pytorchpythongpytorchbayesiangplvm
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