David Held
Assistant Professor at Robotics Institute, Carnegie Mellon University
Pittsburgh, Pennsylvania, United States
Summary
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Senior🎓
Top SchoolDavid Held is an associate professor and robotics researcher with 11 years of experience bridging robotics, computer vision, and machine learning, currently based at Carnegie Mellon University. His work focuses on object manipulation and embodied intelligence, combining deep reinforcement learning and perception systems informed by a PhD from Stanford and postdoctoral work at UC Berkeley. He brings hands-on industry experience from Google X and early robotics research at the Weizmann Institute, which complements a solid engineering foundation in controls from MIT. Known for translating fundamental research into practical robotic manipulation systems, he often blends analytical mechanics intuition with modern learning-based methods. David’s trajectory shows a pattern of tackling hard sensing-to-action problems, and he’s as comfortable designing low-level stiffness models for hyper-redundant arms as developing learning algorithms for real-world robot behavior.
11 years of coding experience
9 years of employment as a software developer
M.S., Mechanical Engineering, M.S., Mechanical Engineering at Massachusetts Institute of TechnologyHigh school, High school at Miami Sunset Senior High SchoolDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Stanford University
English, Hebrew
Github Skills (28)
regression10
ranking9
react8
computer-science8
science8
deep-learning8
jekyll-theme8
jekyll8
pytorch8
openai-gym7
python7
computer-vision7
opencv7
cpp7
cmake6
Programming languages (4)
Github contributions (5)
davheld/precision-tracking
Aug 2014 - Nov 2016
Contributions:68 commits, 3 pushes in 2 years 3 months
davheld/GOTURN
Sep 2016 - Aug 2017
Source code for paper: Learning to Track at 100 FPS with Deep Regression Networks, Held, et al. ECCV 2016
Contributions:15 commits, 6 PRs, 20 pushes in 10 months
pytorchregressionfpsdeep-learningeccv
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