Néstor Subirón-montoro
Engineering at Applied Intuition
Munich, Bavaria, Germany
Summary
🤩
Rockstar🎓
Top SchoolNéstor Subirón-Montoro is an experienced engineering professional with 13 years building simulation and sensor software for autonomous vehicles, currently focused on sensor simulation at Applied Intuition in Munich. He has deep expertise in simulation stacks from leading roles at Argo AI, AID, and as a principal engineer on the CARLA open-source simulator—where he expanded the Python API to make actor, vehicle and sensor control more accessible to researchers. His background in physics (MSc) and early C++ work on precise metrology software give him a strong foundation in mathematical modeling and systems-level implementation. Néstor combines hands-on API and back-end development with technical leadership in production-grade AV tooling, and he often bridges research projects and industrial deployment. An under-the-radar strength is his ability to translate complex simulation primitives (physics, sensors, traffic control) into usable interfaces and example workflows that accelerate adoption across academia and industry.
13 years of coding experience
9 years of employment as a software developer
Master of Science (MSc), Physics, Master of Science (MSc), Physics at University of GroningenLicenciatura, Physics, Licenciatura, Physics at University of Valencia
Spanish, English, Dutch, German
Github Skills (11)
api10
python10
apidoc10
api-design9
cprogramming-language9
c-language9
unreal-engine-47
unreal7
version-control7
git7
unreal-engine-57
Programming languages (8)
Github contributions (5)
carla-simulator/carla
Mar 2017 - May 2020
Open-source simulator for autonomous driving research.
Role in this project:
Back-end Developer & API Implementer
Back-end Developer & API ImplementerContributions:14 releases, 2 reviews, 1581 commits in 3 years 3 months
Contributions summary:Néstor contributed a series of commits primarily focused on expanding the Python API for the CARLA simulator. Key contributions include adding functionality to spawn actors, manipulate their attributes (location, transform, physics), control vehicles, and interface with the simulation environment's features like the weather system and the traffic light system. The user also implemented methods for managing actors, blueprints, and sensors through the Python interface. They also added example scripts to demonstrate the new functionalities. These modifications expanded the capabilities and user accessibility of the API.
deep-reinforcement-learningsimulationcarlasimulatorsimulator-source
nsubiron/configure-pyz
Jun 2014 - Apr 2018
Contributions:3 releases, 34 commits, 14 pushes in 3 years 10 months
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