Juan Gamella is a founder and researcher blending deep mathematical rigor with a decade of engineering experience building highly concurrent, fault-tolerant systems—notably in Erlang/OTP for global-scale payments deployments across APAC, LATAM and Spain. Now pursuing advanced research in robotics, systems and control at ETH Zürich after a PhD-track stint in mathematics and an Apple AI/ML research internship, he seeks to bridge theory and applied systems in research-driven projects. Accustomed to high responsibility in small teams, he has hands-on experience integrating operator billing systems and supporting on-the-ground deployments, alongside mentoring and onboarding engineers. Curious and mathematically oriented, he also cultivates an experimental persona hinted at by his GitHub moniker "Causal Chamber®", signaling an interest in causality and principled ML.
10 years of coding experience
4 years of employment as a software developer
Doctor of Science, MATHEMATICS AND STATISTICS, Doctor of Science, MATHEMATICS AND STATISTICS at ETH Zürich
Master of Science - MS, Robotics, Systems and Control, 5.84/6, Master of Science - MS, Robotics, Systems and Control, 5.84/6 at ETH Zurich
Bachelor of Science, Mathematics and Computer Science, Computer Science, 9.16/10, Bachelor of Science, Mathematics and Computer Science, Computer Science, 9.16/10 at Universidad Politécnica de Madrid
Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search" by David Maxwell Chickering.
Contributions:143 commits, 40 pushes, 2 branches in 1 year 7 months
Contributions:34 commits, 7 pushes, 2 tags in 9 months
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