Qixuan Feng
Senior Research Engineer at Google DeepMind
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolQixuan Feng is a Senior Research Engineer at DeepMind with nine years of applied ML and research experience spanning continual learning, healthcare time-series prediction, and production ML systems. Trained at Oxford and CentraleSupélec, he has moved from academic projects—designing deep architectures for irregular clinical time series—to industrial roles at Optimal Labs, Booking.com, and now DeepMind, where his work bridges cutting-edge research and engineering rigor. He specializes in continual learning and has a track record of taking research ideas into robust implementations for real-world problems. Based in London, he combines strong theoretical grounding (see Google Scholar profile) with practical delivery experience across both startups and large tech. An understated strength is his fluency in turning noisy, irregular data into actionable models—a skill honed in clinical and operational settings.
9 years of coding experience
6 years of employment as a software developer
High School, High School at Beijing N.4 High SchoolMaster’s Degree Computer Science, Master’s Degree Computer Science at University of OxfordEngineer’s Degree computer and electrical engineering, Engineer’s Degree computer and electrical engineering at CentraleSupélecThe first two years of a five-year French engineering degree (which is equivalent to master degree) basic scientific courses: mathematics physics chemistrymechanics electronics computer science, The first two years of a five-year French engineering degree (which is equivalent to master degree) basic scientific courses: mathematics physics chemistrymechanics electronics computer science at Université de Technologie de Compiègne (UTC)
English, French, Chinese, German
Github Skills (55)
probabilistic-programming10
data-science10
statistics10
machine-learning10
deep-learning10
tensorflow10
bayesian-methods10
pytorch9
python9
pandas8
convex7
manipulation7
gpu7
automatic-differentiation7
jax7
Programming languages (4)
Github contributions (5)
qixuanf/uncertainty-baselines
Aug 2021 - Jan 2022
High-quality implementations of standard and SOTA methods on a variety of tasks.
Contributions:50 pushes, 2 branches in 5 months
implementationshigh-qualityvarietyqualitysota
timrudner/S-FSVI
Jul 2022 - Jul 2022
Code to accompany the paper 'Continual Learning via Sequential Function-Space Variational Inference'
Contributions:1 commit, 1 PR, 29 pushes in 1 day
information-theoryautoencoderdeep-learningcontinual-learninginference
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