Ziyu Wang
Technical Staff at Haiper
Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolZiyu Wang is a technical staff machine learning specialist with 13 years of experience bridging cutting-edge research and product-grade AI engineering, now based in Toronto and working at Microsoft AI. He previously held research roles at DeepMind and Google and co-founded Haiper, where he served as CTO and CSO, demonstrating both deep technical leadership and startup execution. Ziyu’s academic pedigree includes a PhD in Machine Learning from Oxford and prior graduate work at UBC, underpinning contributions to probabilistic deep learning—such as enhancements to the popular zhusuan library (normalizing flows, MultivariateNormalCholesky, and sparse GP examples). He excels at turning advanced Bayesian and generative-model ideas into robust code and tests, and is as comfortable debugging libraries as he is shaping research directions. An unexpected thread across his career is consistent involvement in production-focused infrastructure from early banking and cloud research roles to modern ML platform work, giving him rare end-to-end perspective.
13 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of OxfordMasters Computer Science (Machine Learning), Masters Computer Science (Machine Learning) at The University of British ColumbiaHonors Mathematics Computer Science, Honors Mathematics Computer Science at University of Waterloo
English, Chinese
Github Skills (10)
generative-model10
probabilistic-programming10
tensorflow10
python10
gaussian-processes10
deep-learning9
bayesian8
graphical-models8
bayesian-inference8
testing7
Programming languages (5)
Github contributions (5)
thu-ml/zhusuan
May 2017 - Apr 2019
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
Role in this project:
ML Engineer
ML EngineerContributions:17 commits, 7 PRs, 9 pushes in 1 year 11 months
Contributions summary:Ziyu primarily contributed to the development and improvement of probabilistic programming and Bayesian deep learning functionalities within the zhusuan library. They focused on refining existing features like the planar normalizing flow and implemented new distributions such as the MultivariateNormalCholesky. Further contributions included the integration of sparse Gaussian Process (GP) examples and debugging of existing code, alongside relevant testing enhancements.
information-theorydeep-learningbayesian-inferencegraphical-modelsmachine-learning
thu-ml/fpovi
May 2019 - Feb 2022
Code for "Function Space Particle Optimization for Bayesian Neural Networks"
Contributions:10 commits, 8 pushes, 2 branches in 2 years 10 months
particleoptimizationneural-networksbayesian-neural-networksprediction-model
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.