Richard Calland
Machine Learning Engineer at Wayve
Tokyo, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolRichard Calland is a machine learning engineer with 11 years of experience who began his career as a particle physicist and now builds production ML systems that scale from GPU-accelerated research code to web-scale search at companies like Mercari and Wayve. He has deep expertise in GPU optimization and probabilistic modeling from his PhD and postdoc work on neutrino experiments, where he developed Bayesian event reconstruction and reversed-jump MCMC solutions accelerated on GPUs. In industry he’s delivered revenue-driving reranking models, led ML efforts for search and worked on real-time deep-vision systems for autonomous vehicles at Preferred Networks. A practical open-source contributor, he improved dataset handling for the Chainer deep learning framework by adding SVHN support and clarifying tutorials. Based in Tokyo with startup founder experience, he combines research rigor with product-minded engineering to turn cutting-edge methods into reliable production services.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Experimental Particle Physics, Doctor of Philosophy (Ph.D.), Experimental Particle Physics at University of Liverpool
English, Japanese
Github Skills (10)
neural-network10
machine-learning10
deeplearning-ai10
deep-learning10
python10
chainer10
datasets10
numpy9
cuda7
scipy5
Programming languages (5)
Github contributions (5)
chainer/chainer
Jun 2017 - Mar 2018
A flexible framework of neural networks for deep learning
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 5 PRs, 5 comments in 8 months
Contributions summary:Richard's primary contribution involved enhancing the dataset handling capabilities of the Chainer framework. This included implementing the `SVHN` dataset, which involved downloading, preprocessing, and integrating it with the existing MNIST-like functionality. Furthermore, the user made adjustments to the label ordering and provided documentation updates within the tutorial section to improve clarity, alongside small changes to wording and typo fixes.
cudapythonmxnetcaffe2flexible-framework
rcalland/fastLUT
Mar 2016 - Apr 2023
Contributions:7 pushes, 1 branch in 7 years 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.