Daniel Lenton
Founder at unifyai
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolDaniel Lenton is the founder of UnifyAI and a hands-on machine learning and robotics engineer with nine years of experience bridging deep learning research and applied robotics. He holds an MEng and PhD from Imperial College London focused on dense spatial perception for robotic manipulation, and has applied that expertise in roles at Amazon Prime Air and Dyson. Daniel contributes to open-source ML tooling—helping make the ivy project more backend-agnostic and improving PyRep’s robot learning sensors and testing—demonstrating a knack for tooling that moves research into reproducible experiments. He combines low-level numerical improvements (JAX 64-bit, memory efficiency, matmul fixes) with practical robotics integrations (vision sensor enhancements, arm joint utilities), making him effective across research, systems, and product engineering. Based in London, he pairs academic depth with startup grit, often improving developer ergonomics in ways that reveal deep familiarity with both ML frameworks and simulation stacks.
9 years of coding experience
1 year of employment as a software developer
Master’s Degree, MEng Mechanical Engineering, 1st Class Honours, Deans List, Master’s Degree, MEng Mechanical Engineering, 1st Class Honours, Deans List at Imperial College London
Stackoverflow
105reputation
4kreached
3answers
6questions
Github Skills (16)
computer-vision10
machine-learning10
jax10
python10
optimisation10
linear-algebra10
numpy10
optimization10
tensorflow9
pytorch7
ctypes6
nvidia6
cuda6
cmake6
npp6
Programming languages (7)
Github contributions (5)
stepjam/PyRep
Jul 2019 - Aug 2021
A toolkit for robot learning research.
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:11 commits, 14 PRs, 8 comments in 2 years 1 month
Contributions summary:Daniel primarily focused on improving the `pyrep` library, which is a toolkit for robot learning research. Their contributions include fixing bugs related to vision sensor resolution and depth buffer issues, adding functionality to the `Arm` class for retrieving valid joint configurations, and integrating a feature to allow CoppeliaSim to write its stdout to a file instead of the terminal. Furthermore, the user added features related to accessing collection handles and setting render entities within vision sensors, and introduced spherical vision sensors, demonstrating a focus on extending core sensor capabilities. They also contributed to the test suite.
roboticspythonrobot-frameworkrobotrobot-learning
ivy-llc/ivy
Jan 2021 - Oct 2022
Convert Machine Learning Code Between Frameworks
Role in this project:ML Engineer
ML EngineerContributions:9 releases, 791 reviews, 2300 commits in 1 year 9 months
Contributions summary:Daniel added support for the "replace" reduction method for all backends with the "scatter_nd" method. They improved Jax by adding 64-bit datatypes by default, updating the "_to_native" method to recursively check for ivy.Array instances, and getting the Jax tests passing for the Array API isfinite. Furthermore, the user implemented the "all" method, and worked to improve memory efficiency. The user also fixed a bug in the implementation of the "matmul" method.
pythontensorflowframework-learningtemplatedata-science
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