Rob Brekelmans

Postdoctoral Fellow at Vector Institute

Old Toronto, Ontario, Canada
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Summary

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Senior
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Rob Brekelmans is a postdoctoral fellow at the Vector Institute in Toronto with nine years of experience bridging academic research and practical rigor in AI and quantitative trading. He earned a PhD in Computer Science from USC’s Information Sciences Institute after an MSc at Imperial College and a multidisciplinary BA in Mathematics and Chinese from Penn, and has worked on AI safety as a research intern at DeepMind. His background includes four years as an options trader, giving him a rare combination of probabilistic modeling skills, research depth, and risk-aware decision-making. At Vector he collaborates with leading researchers on foundational ML problems, bringing both theoretical insight and hands-on experimentation to bear. Fluent in Mandarin and experienced across industry and academia, he often applies cross-disciplinary perspectives to hard problems in machine learning and safety.
code9 years of coding experience
bookMaster of Science (MSc), Computing Science, Master of Science (MSc), Computing Science at Imperial College London
bookDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of Southern California
bookMath, Science & Technology, Math, Science & Technology at DuPont Manual High School
bookMandarin Chinese, Mandarin Chinese at CET Beijing Chinese Language Program
bookBA, Mathematics, Chinese Language, BA, Mathematics, Chinese Language at University of Pennsylvania
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Github Skills (13)

mutual-information9
information-theory8
data-science7
python7
pytorch7
machine-learning7
deep-learning6
tensorflow6
jax5
directed-acyclic-graph3
graph3
data-cleaning2
chrome-extension1

Programming languages (2)

JavaScriptPython

Github contributions (5)

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brekelma/dsbox_corex

Mar 2018 - Feb 2022

Contributions:6 PRs, 185 pushes, 6 branches in 3 years 11 months
kxh001/ITdiffusion

Feb 2023 - Feb 2023

Information-Theoretic Diffusion: A brand new diffusion model / density estimator based on information theory.
Contributions:37 commits in 1 day
information-theory
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