Lev Givon
Senior Data Scientist
Greater Pittsburgh Region United States
Summary
🤩
Rockstar🎓
Top SchoolLev Givon is a Senior Data Scientist with 17 years of experience who blends deep academic research in computational neuroscience with industrial-scale machine learning and GPU-accelerated computing to advance drug development and digital health at Johnson & Johnson. He built widely used open-source tools (Neurokernel, NeuroArch) during his PhD to enable collaborative, multi-GPU brain modeling and continues to contribute low-level CUDA/Python work—evident in GPU-focused projects like scikit-cuda and conda build tooling. His background spans signal processing, graph databases for biological data, and production ML for IoT, materials, and clinical biomarker prediction, giving him a rare combination of domain depth and systems-level engineering. Colleagues rely on him for translating incomplete biological data into executable models and for optimizing compute pipelines that turn large, heterogeneous datasets into actionable insights.
17 years of coding experience
20 years of employment as a software developer
Bachelor of Science (BS), Electrical Engineering, Computer Science, Bachelor of Science (BS), Electrical Engineering, Computer Science at Columbia University - Fu Foundation School of Engineering and Applied ScienceMaster of Philosophy (MPhil), Electrical Engineering, Master of Philosophy (MPhil), Electrical Engineering at Columbia University in the City of New YorkMaster of Science (MS), Electrical Engineering, Master of Science (MS), Electrical Engineering at Columbia Engineering
Stackoverflow
1,381reputation
72kreached
18answers
24questions
Github Skills (24)
environmental10
python10
scripting10
gpu-programming10
conda10
bash10
cusolver10
script10
manage10
build-automation10
management10
cuda10
sh10
shell10
linear-algebra10
Programming languages (23)
Github contributions (5)
lebedov/scikit-cuda
Apr 2010 - Mar 2022
Python interface to GPU-powered libraries
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 releases, 882 commits, 68 PRs in 12 years 1 month
Contributions summary:Lev's contributions primarily involve the development of the CUDA SciKit, focusing on providing Python interfaces for GPU-powered libraries. They implemented wrappers for various CULA and CUSOLVER functions, enabling the use of these libraries for linear algebra operations such as SVD, QR decomposition, and solving linear systems. Their work also included enabling the usage of CUDA streams and improving the documentation of the functions they implemented, reflecting their work on the backend to leverage GPUs.
cudalapackgpu-programmingpythongpu-acceleration
conda-archive/conda-recipes
Oct 2015 - Jan 2016
build and test recipes for conda
Role in this project:DevOps Engineer & Backend Developer
DevOps Engineer & Backend DeveloperContributions:6 commits, 3 PRs, 2 comments in 2 months
Contributions summary:Lev primarily focused on enhancing the build process and environment setup for conda recipes. Their work involved adding scripts to manage environment variables and prefixes, essential for the proper functioning of the openmpi recipe. They also made changes to build scripts, and adjusted build configurations to optimize the build process, ensuring consistent behavior across platforms. Additionally, they merged master branches, indicating a role in maintaining the repository's overall health.
recipespythoncondasetuptoolsanaconda
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