Daniel Shats
MLE at Wayve
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolDaniel Shats is a machine learning engineer with nine years of experience specializing in deep learning and embodied AI, currently building end-to-end driving models at Wayve in the San Francisco Bay Area. He has a strong research background from IBM where he worked on multimodality and AI-driven drug development, and earlier contributed to medical imaging and COVID causal-inference projects, including the WNTRAC database. Daniel combines academic rigor from Technion (MS) and University of Florida (BS in CS and Math) with practical engineering—shipping vision systems, benchmarking tools, and a consumer app as a founder. Notably, his KiTS21 efforts earned a best-paper award and a top competition placement, illustrating an ability to translate research into competitive, real-world systems.
9 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Technion - Israel Institute of TechnologyBachelor of Science - BS, Computer Science (with a second degree in Mathematics), Bachelor of Science - BS, Computer Science (with a second degree in Mathematics) at University of Florida
Github Skills (65)
modular10
ai10
mojo10
code-reuse9
pretrain9
fuse9
programming-language9
python9
max9
deep-learning9
medical9
medical-imaging9
pytorch9
machine-learning9
data-science9
Programming languages (12)
Github contributions (5)
smartdanny/smartdanny.github.io
Feb 2017 - Jan 2021
Contributions:53 pushes, 1 branch in 4 years
smartdanny/ChessGameOfficial
Feb 2017 - Dec 2018
This is the official Repository for the COP3503 Group_33 Chess Game
Contributions:2 PRs, 2 pushes, 1 branch in 1 year 10 months
javascript
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