Saran Tunyasuvunakool
Senior Staff Research Engineer at Google DeepMind
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolSaran Tunyasuvunakool is a Senior Staff Research Engineer at Google DeepMind in London with 11 years of experience, responsible for stewarding the widely used MuJoCo physics engine and its surrounding simulation stack. He moved from a PhD in black hole simulations to building production-grade physics and RL infrastructure, uniquely bridging scientific modelling and scalable engineering. His strengths are backend development and performance optimization, including native resource management, rendering context improvements and a plugin mechanism for actuators and sensors. He is an active open-source maintainer who combines bug fixes, documentation, and low-level refactoring with practical fixes—down to a macOS VSync workaround and UI tweaks—for real-time control tools. Pragmatic and detail-oriented, he focuses on making simulation tooling robust, reproducible and production-ready for research and robotics applications.
11 years of coding experience
6 years of employment as a software developer
University of CambridgeCertificate in Science, Mathematics, Certificate in Science, Mathematics at University of CanterburyHigh School, High School at Burnside High School
English, Thai
Stackoverflow
1,089reputation
62kreached
13answers
13questions
wifi
top-5%
Github Skills (26)
simulation10
c-language10
documentations10
python10
simulator10
simulations10
plugin-development10
physics10
performance-optimization10
mujoco10
documentation10
c-programming-language10
reinforcement-learning9
wifi9
refactoring8
Programming languages (10)
Github contributions (5)
google-deepmind/mujoco
Oct 2021 - Jan 2023
Multi-Joint dynamics with Contact. A general purpose physics simulator.
Role in this project:
Back-end Developer & Documentation Specialist
Back-end Developer & Documentation SpecialistContributions:12 releases, 116 reviews, 112 commits in 1 year 3 months
Contributions summary:Saran primarily focused on addressing documentation issues and implementing bug fixes within the MuJoCo physics simulator. Their contributions included correcting license links, updating changelogs, and resolving code formatting issues. Furthermore, the user was involved in refactoring the low-level implementation details.
physics-enginephysicsroboticsrobotics-simulationbullet-physics
google-deepmind/dm_control
Jan 2018 - Dec 2022
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Role in this project:Back-end Developer
Back-end DeveloperContributions:16 releases, 7 reviews, 110 commits in 4 years 11 months
Contributions summary:Saran made significant contributions to the `dm_control` library, focusing on improvements related to MuJoCo physics simulation and reinforcement learning environments. Their work included adding methods for freeing native resources, implementing error handling, and enhancing the functionality of rendering contexts. The user also implemented a plugin mechanism for actuators and sensors, demonstrating a deep understanding of the underlying MuJoCo integration within the library. Furthermore, the user focused on performance optimizations within the simulation.
simulationreinforcementsoftware-stackphysics-based-simulationsimulation-based
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