Benjamin Ellenberger is a Lead Data Scientist in Bern with 11 years of experience bridging software engineering, machine learning and computational neuroscience to build production-ready AI systems for healthcare. Trained at ETH Zurich (MSc) and a PhD candidate in computational neuroscience at Universität Bern, he leads a 15-person data analytics team at Insel, delivering clinical decision support, dashboards and ML-driven patient-safety indicators via Epic and an in-house "Turing" platform. He combines deep engineering skills in Java and Python with hands-on experience in deep learning, optimization and RL, and contributes to notable open-source projects like Bullet Physics and pybullet-gym that highlight his work on simulation and reinforcement learning tooling. Known for turning research-grade models into robust, operational data products, he blends academic rigor with pragmatic system design to accelerate evidence-based clinical decisions.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Science (B.Sc.), Computer Science, Bachelor of Science (B.Sc.), Computer Science at University of Zurich
Doctor of Philosophy - PhD, Computational Neuroscience, Doctor of Philosophy - PhD, Computational Neuroscience at Universität Bern
Master of Science (M.Sc.), Neural Systems and Computation, Master of Science (M.Sc.), Neural Systems and Computation at ETH Zurich
Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
Role in this project:
Back-end Developer
Contributions:41 commits, 14 PRs, 40 pushes in 3 years 3 months
Contributions summary:Benjamin primarily focused on modifying and refactoring the code within the pybullet-gym repository. Their contributions involved moving files, refactoring code related to joints, and implementing changes to humanoids. The user also appears to be involved in updating the environment to match the behavior in Roboschool. They added a setup.py for easy installation.
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
Role in this project:
Back-end Developer
Contributions:63 commits, 29 PRs, 241 comments in 2 years 9 months
Contributions summary:Benjamin appears to be involved in debugging and improving the Bullet Physics SDK, specifically addressing issues related to raycasting and slider functionality within example projects. Their contributions include fixing a raycast sample and adding missing calls in a slider, as well as integrating external code merges. They also added new examples to the example browser. These changes suggest a focus on refining the core functionality and usability of the physics engine.
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