James Heald
Research Fellow In Theoretical Neuroscience at UCL
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolJames Heald is a Research Fellow in Theoretical Neuroscience at the Gatsby Unit, UCL, with a decade of experience building and analyzing intelligent motor control systems using reinforcement learning and probabilistic ML. He develops novel model-based RL and representation-learning methods for high-dimensional control, and has trained agents for dexterous manipulation in MuJoCo—winning the NeurIPS 2024 MyoChallenge on Dexterity in Bionic Humans. His prior work includes a Nature-published computational model of motor learning developed during a postdoc at Columbia, drawing on Bayesian nonparametrics, hierarchical modeling, and sequential Monte Carlo. Trained as both an engineer (PhD, Cambridge) and a medical doctor (MBChB), he uniquely bridges clinical insight with rigorous computational methods. He is active in open research with a public website and GitHub presence, focusing on transfer and imitation learning that link biologically plausible theories to practical robotic control. Colleagues describe him as someone who turns theoretical ideas into competitive, real-world agents.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Medicine, Bachelor of Surgery - MBChB, Medicine, Bachelor of Medicine, Bachelor of Surgery - MBChB, Medicine at The University of ManchesterDoctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at University of CambridgeMaster of Science - MSc (Distinction), Cognitive and Computational Neuroscience, Master of Science - MSc (Distinction), Cognitive and Computational Neuroscience at The University of Sheffield
Github Skills (43)
simulation10
physics-engine10
deterministic10
robotics10
toolbox10
simulator10
openai-gym10
machine-learning10
inference10
diffusion-probabilistic-models10
dynamics10
bullet-physics10
mechanics10
physics10
robot-simulator10
Programming languages (6)
Github contributions (5)
jamesheald/myosuite
Sep 2024 - Feb 2026
MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.
Contributions:76 pushes, 8 branches, 1 comment in 1 year 5 months
jamesheald/SSSM
Jan 2018 - Oct 2022
Contributions:2 PRs, 105 pushes, 5 branches in 4 years 8 months
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