Shay Ohayon
Research Scientist at Meta
Livermore, California, United States
Summary
👤
Senior🎓
Top SchoolShay Ohayon is a research scientist with 13 years of cross-disciplinary experience at the intersection of computer vision, neuroscience, and machine learning, currently improving perception algorithms at Meta Reality Labs. Trained as a neuroscientist (PhD, Caltech) and computer scientist (Technion), he combines experimental rigor with hands-on engineering to build novel instrumentation, algorithms, and scalable systems. His background spans academic micro-endoscope design and viral targeting in primates to industrial R&D at Google on detection, tracking, and synthetic data, and practical productization as the founder of an embedded wearable startup. He has shipped production-grade medical imaging algorithms and contributed to open-source electrophysiology tooling by fixing low-level data and type issues that improved cross-tool compatibility. Based in Livermore, CA, Shay also applies precision engineering outside software—having designed, built, and test-flown a four-seat airplane—reflecting a maker’s approach to solving hard problems end-to-end.
13 years of coding experience
10 years of employment as a software developer
Master's Degree Computer Science, Master's Degree Computer Science at Technion - Israel Institute of TechnologyPostdoc Neuroscience, Postdoc Neuroscience at Massachusetts Institute of TechnologyCalifornia Institute of Technology
English, Hebrew
Stackoverflow
161reputation
16kreached
2answers
7questions
Github Skills (12)
c-language10
cprogramming-language10
file-handling9
amazon-cloudwatch6
bootstrap-modal6
xamarin6
php6
driver6
mongodb6
apache6
apple-watch6
opengl6
Programming languages (10)
Github contributions (5)
open-ephys/GUI
Nov 2012 - Feb 2015
Software for electrophysiology data acquisition (deprecated)
Role in this project:
Backend Developer
Backend DeveloperContributions:11 commits, 1 push, 12 comments in 2 years 3 months
Contributions summary:Shay primarily focused on fixing type casting errors and code compilation issues. They addressed ambiguities in type casting operations by removing them and explicitly casting variables to double. Additionally, the user modified file handling in the record node, changing the fopen mode to binary. This ensures that the recorded data is correctly formatted and parsed in external applications.
data-acquisitionpythoncomputational-neuroscienceelectrophysiology-dataopen-science
shayo/Kofiko
Apr 2015 - Jan 2020
Contributions:5 commits, 1 PR, 4 pushes in 4 years 10 months
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