Alex Bewley
Senior Research Scientist at Google DeepMind
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolAlex Bewley is a Senior Research Scientist at Google DeepMind with a decade of experience applying deep learning, computer vision, simulation and reinforcement learning to real-world robotics and autonomous systems. His career spans academic postdoctoral work at Oxford, industrial research roles at Wayve and Google, and hands-on engineering in embedded and automation systems—giving him rare end-to-end expertise from sensor-level systems to large-scale ML research. He led sim-to-real efforts that bridged simulation research and physical deployment, mentored numerous students and interns, and has a track record of collaborating with industry partners in mining and autonomy. Based in Zurich, he combines rigorous academic training (PhD, postdoc) with pragmatic startup and production experience, and describes his mission succinctly on GitHub as “Doing my bit to bring the future closer.”
11 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy (PhD), Electrical, Electronics and Communications Engineering, Doctor of Philosophy (PhD), Electrical, Electronics and Communications Engineering at QUT (Queensland University of Technology)Postdoc, Postdoc at University of OxfordThe University of Sydney
Github Skills (38)
realtime10
sequence10
matlab9
python9
machine-learning9
image-translation9
few-shot-learning9
paper9
adversarial-learning9
adaptation9
transfer-learning9
transformer-architecture8
deep-learning8
tensorflow8
datasets8
Programming languages (5)
Github contributions (5)
abewley/sort
Feb 2016 - Jul 2022
Simple, online, and realtime tracking of multiple objects in a video sequence.
Contributions:45 commits, 1 PR, 43 pushes in 6 years 6 months
realtimesequencesimple-online-and-realtime-trackingrealtime-trackingtracking
google-research/human-scene-transformer
Sep 2023 - Oct 2023
Human Scene Transformer: A framework for trajectory prediction and wrappers for reframing the JRDB dataset for the prediction task.
Contributions:1 review, 6 PRs, 5 pushes in 29 days
deep-learningtrajectory-predictiontransformer-architecturetensorflow2
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