Michael Kaminsky
Chief Science Officer And Founder at Carnegie Mellon University
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolMichael Kaminsky is a founder-scientist and systems researcher with 14+ years of experience designing scalable distributed systems, low-latency networking, and efficient infrastructure for ML and visual data. As Chief Science Officer at BrdgAI he applies satellite and edge vision pipelines to optimize ranching for carbon sequestration and cattle health, pairing novel large-scale labeling techniques with on-site inference and intelligent data transfer. An adjunct faculty member at Carnegie Mellon and former Intel Labs research lead, he has driven nearly 100 publications and chaired top systems conferences (including SOSP 2013). He mixes deep academic rigor (PhD from MIT) with hands-on engineering—contributing to open-source projects like high-performance concurrent hash tables and building both backend systems and data-visualization tooling. His work repeatedly bridges cloud, edge, and sensor networks to turn research prototypes into practical deployments.
14 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of California, BerkeleyMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Massachusetts Institute of Technology
Github Skills (14)
jupyter-notebook10
c-language10
cprogramming-language10
python10
makefile9
data-visualisation9
gnu-make9
data-visualization9
data-visualizations9
json9
configurations8
configuration-management8
testing8
configuration-file8
Programming languages (6)
Github contributions (5)
efficient/libcuckoo
Jan 2016 - Dec 2016
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:9 commits, 2 comments, 1 issue in 11 months
Contributions summary:Michael contributed to both the backend and frontend aspects of the project. They fixed a compile error, likely in the backend codebase. They also implemented a Jupyter/IPython notebook for plotting results and improved its capabilities, indicating work on the frontend or data visualization. Furthermore, the user modified the build process and the JSON output structure, demonstrating involvement in project configuration and data handling.
multithreadingconcurrent-programmingconcurrencyhashrust
efficient/paper_skel
May 2014 - Mar 2019
Contributions:9 commits, 8 pushes in 4 years 11 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.