Lane Mcintosh
Senior Staff Machine Learning Scientist at Tesla
Palo Alto, California, United States
Summary
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Senior🎓
Top SchoolLane Mcintosh is a Senior Staff Machine Learning Scientist at Tesla leading teams that train foundation visual networks used by millions of Autopilot customers. With 13 years of experience bridging theoretical neuroscience, mathematics, and computer vision, he translated PhD research on deep models of early vision at Stanford into production-scale autonomous driving systems. He has led object-detection efforts and published research and practical architectures (including work from a Google Brain internship) that balance speed and accuracy in scene understanding. Lane’s background in information theory and statistical mechanics informs a principled approach to robust perception for distributed robotics. Based in Palo Alto, he combines academic rigor—NVIDIA Best Poster and NeurIPS publications—with hands-on delivery of large-scale ML systems.
13 years of coding experience
14 years of employment as a software developer
M.A. Mathematics, M.A. Mathematics at University of Hawaii at ManoaB.A. Neurobiology Computational Neuroscience, B.A. Neurobiology Computational Neuroscience at University of ChicagoDoctor of Philosophy (PhD) Neurosciences and Computer Science, Doctor of Philosophy (PhD) Neurosciences and Computer Science at Stanford University
Stackoverflow
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0reached
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Github Skills (18)
pytorch10
convolutional-neural-networks10
python10
data-science10
machine-learning10
deep-learning10
tensorflow10
jax10
hdf9
mutual-information9
electrophysiology9
matlab8
neuroscience8
clustering7
scientific-computing6
Programming languages (3)
Github contributions (5)
baccuslab/gknn-entropy
Apr 2014 - Dec 2015
Contributions:15 commits in 1 year 8 months
baccuslab/shannon
Jun 2015 - Nov 2017
A python package for computing the mutual information and entropy for continuous and discrete data.
Contributions:16 commits, 14 pushes, 1 branch in 2 years 5 months
mutual-informationpython
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