Avishkar Bhoopchand
Staff Research Engineer at Google DeepMind
London, England, United Kingdom
Summary
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Senior🎓
Top SchoolAvishkar Bhoopchand is a Staff Research Engineer at DeepMind with 12 years of experience bridging machine learning research and production-grade software engineering. He works on game theory and multi-agent problems and recently applied large language models to build a pedagogical tutor chatbot for YouTube, alongside prior large-scale multi-agent RL and COVID modelling work. His publications include papers in Nature Communications and contributions to online learning and gated linear networks, and he published the DELVE Global Covid-19 Dataset while seconded to Oxford. With a background as a full‑stack analyst developer in finance and certification as a Financial Risk Manager, he brings strong systems thinking and risk-aware engineering to ML research. Based in London, he is a long-standing leader in African AI development as an executive board member and co-general chair of the Deep Learning Indaba, where he oversaw a $500k budget and built scalable event infrastructure. He combines academic rigor, production experience, and community-building—often turning research prototypes into real-world tools and datasets.
12 years of coding experience
7 years of employment as a software developer
Financial Risk Manager FRM Level 1 and 2, Financial Risk Manager FRM Level 1 and 2 at Global Association of Risk ProfessionalsBachelor of Business Science Computer Science, Bachelor of Business Science Computer Science at University of Cape TownGraduate Diploma in Mathematics, Graduate Diploma in Mathematics at University of LondonUniversity College LondonMatric Senior Certificate, Matric Senior Certificate at South African College High School
English, Afrikaans
Stackoverflow
929reputation
32kreached
15answers
0questions
tensorflow
top-5%
Github Skills (19)
artificial-intelligence10
docker10
web-application10
corona10
python10
machine-learning10
large-scale10
datasets10
scale10
deep-learning10
baobab10
flask10
multi-tenant10
tensorflow9
lstm6
Programming languages (2)
Github contributions (5)
deep-learning-indaba/Baobab
Jan 2019 - Jan 2023
Baobab is an open source multi-tenant web application designed to facilitate the application and selection process for large scale meetings within the machine learning and artificial intelligence communities globally. Supported by the Deep Learning Indaba
Contributions:241 reviews, 1591 commits, 1107 PRs in 4 years 1 month
multi-sourcetenantpythonflaskweb-application
rs-delve/covid19_datasets
Apr 2020 - May 2022
Interfacing several COVID-19 related datasets
Contributions:1 review, 969 commits, 21 PRs in 2 years 1 month
datasetsdataset
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