Vinay Ramakrishnaiah
Senior Member Of Technical Staff at AMD
Redmond, Washington, United States
Summary
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Rockstar🎓
Top SchoolVinay Ramakrishnaiah is a Senior Member of Technical Staff at AMD with nine years of experience blending research-grade HPC, AI, and signal-processing expertise into practical architectures for graph analytics and exascale systems. He holds a PhD focused on applying high-performance computing to wireless networks and has led scalable machine learning and proxy-app efforts at Los Alamos, including a reinforcement-learning framework (EXARL) for the ECP. Vinay contributes to the widely used Spack package manager, maintaining and packaging scientific software—showing a hands-on commitment to reproducible, portable HPC software. Based in Redmond, he combines deep algorithmic research with production-minded engineering across heterogeneous platforms, and has a track record of mentoring and co-design education that amplifies his technical impact.
9 years of coding experience
8 years of employment as a software developer
Master of Science (M.S.), Antennas in Ad Hoc networks, 4.0, Master of Science (M.S.), Antennas in Ad Hoc networks, 4.0 at University of WyomingBachelor of Engineering (BE), Electronics and Communications Engineering, 9.79/10, Bachelor of Engineering (BE), Electronics and Communications Engineering, 9.79/10 at Malnad College of Engineering, HASSAN
English, Hindi, Kannada
Github Skills (8)
package-manager-tool10
build-tools10
package-manager10
package-management10
python10
scientific-computing10
hpc8
mpi8
Programming languages (5)
Github contributions (5)
spack/spack
Sep 2018 - Oct 2020
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 reviews, 44 commits, 67 PRs in 2 years
Contributions summary:Vinay primarily contributes to the Spack package manager by creating and updating package definitions. They have created packages for software such as Ember, PICSARlite, Thornado-mini, and various Python packages. Their work involves defining dependencies, build processes, and installation procedures for scientific software within the Spack ecosystem. They also bump the versions of existing packages.
compilerspythonradiussplatformslinux
exalearn/EXARL
Dec 2019 - Jul 2022
Scalable Framework for Reinforcement Learning
Contributions:25 reviews, 1078 commits, 26 PRs in 2 years 7 months
scalablereinforcement-learningdeep-reinforcement-learningreinforcementq-learning
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