Sjoerd Van Steenkiste
Senior Research Scientist at Google DeepMind
San Francisco, California, United States
Summary
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Senior🎓
Top SchoolSjoerd Van Steenkiste is a Senior Research Scientist with a decade of experience advancing foundational deep learning at Google and Google DeepMind, following a PhD and postdoc in IDSIA under Jürgen Schmidhuber. He blends rigorous academic research in structured neural representations and visual reasoning with practical engineering—contributing visualization tooling to the popular Brainstorm neural network library to make training dynamics more accessible. Based in the San Francisco Bay Area, he has a track record of moving ideas from theory to interactive demos and production research across internships and staff roles. His background in operations research and knowledge engineering gives him a distinctive systems-oriented perspective on model design and evaluation.
10 years of coding experience
9 years of employment as a software developer
Master of Science (MSc) Artificial Intelligence, Master of Science (MSc) Artificial Intelligence at Maastricht UniversityDoctor of Philosophy (PhD) Artificial Intelligence, Doctor of Philosophy (PhD) Artificial Intelligence at USI Università della Svizzera italiana
Dutch, English, German
Github Skills (6)
neural-network10
machine-learning10
visualization10
bokeh10
visualizations10
python10
Programming languages (3)
Github contributions (5)
IDSIA/brainstorm
Sep 2015 - Oct 2015
Fast, flexible and fun neural networks.
Role in this project:
ML Engineer
ML EngineerContributions:13 commits, 5 PRs, 5 comments in 1 month
Contributions summary:Sjoerd primarily contributed to the visualization aspects of the Brainstorm neural network library. They added and refined a Bokeh-based visualization hook, enabling users to monitor accuracy during training with interactive plots. Their work includes refactoring the existing visualization hook and adding features such as support for streaming data and saving the visualizations to HTML files. They also made minor documentation improvements.
deep-learningneural-networksmachine-learningneural-networktensorflow
sjoerdvansteenkiste/Neural-EM
Aug 2017 - Nov 2019
Code for the "Neural Expectation Maximization" paper.
Contributions:6 commits, 4 pushes, 9 comments in 2 years 3 months
pytorchmaximizationexpectation-maximizationexpectation
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