Oier Mees
Machine Learning Engineer
Berkeley, California, United States
Summary
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RockstarOier Mees is a robotics and machine learning researcher-turned-lecturer with 15 years of experience bridging academic research and industry innovation, currently teaching "Robot Learning: From Fundamentals to Foundation Models" at ETH Zürich while leading Robot Learning & Foundation Models at Microsoft. He completed a postdoc at Berkeley AI Research (RAIL/BAIR) under Sergey Levine and earned a PhD in Robot Learning from Freiburg, blending deep expertise in control, perception (including Visual SLAM), and learning-based robotics. His background spans internships and research roles at NVIDIA, Fraunhofer, and several European labs, giving him hands-on experience with real-world robotic systems and teleoperation. Known for translating cutting-edge research into curriculum and product directions, he often works at the intersection of foundation models and embodied intelligence—a less obvious thread running through both his teaching and industrial leadership.
15 years of coding experience
Github Skills (99)
benchmark10
deep-learning10
representation-learning10
robotics10
computer-vision10
pybullet10
tensorflow10
natural-language-processing10
pytorch10
horizon10
robot10
vision-and-language10
caffe9
pretrain9
ai9
Programming languages (9)
Github contributions (5)
mees/generalize_spatial_relations
Nov 2019 - Feb 2021
Code for the paper "Metric Learning for Generalizing Spatial Relations to New Objects" (IROS 2017)
Contributions:16 commits, 15 pushes, 1 branch in 1 year 2 months
metric-learning
mees/vapo
Sep 2021 - Apr 2022
[ICRA 2022] Implementation of Affordance Learning from Play for Sample-Efficient Policy Learning
Contributions:28 commits, 21 pushes, 1 branch in 6 months
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