Ruben D'sa

Sr. Product Manager - Simulation Framework For Robot Learning

San Francisco, California, United States
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Summary

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Rockstar
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Top School
Ruben D'sa is a senior product manager and robotics researcher with 12 years of experience building simulation, control, and hardware systems for aerial and humanoid robots. Currently leading Isaac Lab’s simulation experience at NVIDIA, he blends product leadership with deep technical expertise from roles at OpenAI, Talos Robotics, and hands-on research developing a transformable solar-powered aircraft at the University of Minnesota. His work spans system dynamics, power electronics, and energy-aware vehicle design, with a knack for squeezing maximal performance through principled modeling, control, and estimation. Ruben has founded a consulting/IP company and shipped robotics infrastructure and simulation platforms for real-world integration, bridging academic prototypes and production-grade tooling. Based in San Francisco, he pairs a Ph.D.-level understanding of multidisciplinary systems with practical delivery experience across startups and research labs. An under-the-radar strength is his track record of improving measurement and automation fidelity—evident from past projects that dramatically increased data resolution and reduced test times.
code12 years of coding experience
job13 years of employment as a software developer
bookDoctor of Philosophy (Ph.D.) Robotics, Doctor of Philosophy (Ph.D.) Robotics at University of Minnesota
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Github Skills (55)

scroll10
smooth-scrolling9
simulation9
physics-engine9
simulations9
mouse9
smooth9
mujoco9
robotics-simulation8
urdf8
reverse8
boost8
reader8
language-server8
compile8

Programming languages (6)

TypeScriptC++JavaScriptSwiftCythonPython

Github contributions (5)

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rubendsa/rubendsa.github.io

Mar 2019 - Oct 2024

Contributions:3 PRs, 78 pushes, 2 branches in 5 years 8 months
rubendsa/MIST-Bullet

Mar 2019 - Jan 2021

Contributions:69 pushes, 8 branches in 1 year 10 months
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Ruben D'sa - Sr. Product Manager - Simulation Framework For Robot Learning