Ankesh Anand
Research Scientist at Google DeepMind
London, England, United Kingdom
Summary
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Senior🎓
Top SchoolAnkesh Anand is a Research Scientist at Google DeepMind in London with 13 years of experience bridging deep learning research and production software. He completed a PhD in Machine Learning at Université de Montréal / MILA after an Integrated MSc in Mathematics and Computing from IIT Kharagpur, and his trajectory includes research internships at DeepMind, Google, and Microsoft alongside earlier software engineering roles at Visa and HackerEarth. Ankesh focuses on reinforcement learning and deep learning methods, bringing both academic rigor and practical engineering experience to large-scale ML problems. Notably, his path from production-facing software roles to MILA’s PhD program highlights a pragmatic mindset: building systems that are not only scientifically novel but also deployable. Based in London, he combines international research collaborations with hands-on contributions to cutting-edge AI initiatives at DeepMind.
13 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at Université de MontréalIntegrated MSc, Mathematics and Computing, Integrated MSc, Mathematics and Computing at Indian Institute of Technology, Kharagpur
English, Hindi
Stackoverflow
1,705reputation
165kreached
2answers
13questions
Github Skills (141)
python10
visa10
deep-learning10
representation-learning10
robotics10
gfycat10
self-supervised-learning10
computer-vision10
reinforcement-learning10
information-theory10
tensorflow10
pytorch10
data-efficient10
machine-learning10
ml9
Programming languages (7)
Github contributions (5)
ankeshanand/deep-clickbait-detection
Sep 2016 - Sep 2018
Contributions:5 commits, 2 pushes in 1 year 11 months
mila-iqia/atari-representation-learning
Jan 2019 - Aug 2021
Code for "Unsupervised State Representation Learning in Atari"
Contributions:362 commits, 5 PRs, 98 pushes in 2 years 7 months
representation-learning
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