Igor Ganichev
Quantitative Researcher
Berkeley, California, United States
Summary
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Rockstar🎓
Top SchoolIgor Ganichev is a quantitative researcher based in Berkeley with nine years of professional experience bridging cutting-edge machine learning infrastructure and low-level systems engineering. After a PhD at UC Berkeley on multipath routing and SDN, he spent years shaping network virtualization and core messaging platforms at Nicira and VMware before moving to Google Brain/TensorFlow as a senior software engineer. Since 2020 he has applied that blend of systems and ML expertise at a private hedge fund, developing quantitative models informed by deep experience in large-scale distributed systems. His background includes optimizing custom compilers, building troubleshooting tools for multi-thousand-node clusters, and shipping production-grade networking features—skills that give him an unusual edge in making ML and trading systems both performant and debuggable. Trained at MIT in both computer science and mathematics, he combines theoretical rigor with pragmatic engineering for high-stakes production environments.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of California, BerkeleyBachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Massachusetts Institute of Technology
Github Skills (25)
python10
data-science10
machine-learning10
ml10
deep-learning10
tensorflow10
deep-neural-networks10
neural-network10
gpu8
statistics7
bayesian-methods7
optimization6
probabilistic6
parallel6
numpy5
Programming languages (5)
Github contributions (5)
google/cog
Jul 2018 - Oct 2018
Contributions:6 commits, 5 pushes, 1 branch in 3 months
iganichev/scratch
Jan 2017 - Dec 2017
Contributions:7 pushes, 1 branch in 11 months
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