Jishnu Mukhoti
AI Lead, Founding Team at Finster AI
Oxford, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolJishnu Mukhoti is an AI lead and founding-team technologist with 9 years of experience, currently building agents at Finster to fuse disparate financial and market data for faster decision-making. He combines deep research pedigree—pursuing a DPhil at Oxford under Philip Torr, Yarin Gal and Puneet Dokania—with hands-on industry experience from Meta/Facebook AI internships and a software engineering background at Amazon. His work spans scalable multimodal models, robustness to out-of-distribution data, and practical ML deployments, reflecting a focus on both performance and safety in real-world systems. Notably, he pairs startup product work with ongoing academic research, bringing rigorous probabilistic and uncertainty-aware methods to financial AI.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of OxfordBachelor of Computer Science and Engineering Computer Science and Engineering, Bachelor of Computer Science and Engineering Computer Science and Engineering at Jadavpur University
Bengali, Hindi, English
Github Skills (15)
approximation10
loss-functions10
loss10
dropout10
bayesian9
uncertainty9
visual-recognition8
deterministic6
deep-learning6
bayesian-deep-learning6
ensembles5
machine-learning3
deep-neural-networks3
pii1
uncertainty-quantification1
Programming languages (3)
Github contributions (5)
omegafragger/DropoutUncertaintyExps
Jun 2018 - Oct 2018
Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
Contributions:28 commits, 21 pushes, 2 branches in 4 months
deep-learningdropoutapproximationuncertaintybayesian
omegafragger/omegafragger.github.io
Nov 2018 - Oct 2019
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Contributions:88 pushes in 10 months
templategithub-pages-templatemmistakesmistakesjekyll
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