Gulsum Akbulut
Member Of Technical Staff at AMD
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolGulsum Akbulut is a Member of Technical Staff at AMD on the JAX machine learning frameworks team, specializing in enabling and optimizing JAX for AMD ROCm platforms to ensure compatibility and high performance across diverse hardware. She holds a Ph.D. in Computer Engineering from Penn State, where her research focused on performance optimization, energy efficiency, dynamic multi-GPU scheduling, and compiler-guided tuning for multithreaded workloads—expertise she applies to real-world ML scalability challenges. With nine years of experience spanning research, internships at Intel and AMD, and substantial open-source contributions, she helps maintain ROCm MaxText and has added GPU resource management features to widely used projects like Galaxy. Based in Austin, she combines deep systems-level research with hands-on framework work, and is passionate about improving reliability and performance through community-driven engineering.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at Penn State UniversityUndergraduate, Computer Engineering, Undergraduate, Computer Engineering at Bilkent UniversityInternational BaccalaureateInternational Baccalaureate, International Baccalaureate at Bilkent Laboratory & International School
Spanish, English, Turkish, French
Github Skills (8)
cuda10
bioinformatics10
galaxy10
genomics10
workflow-engine10
gpu10
python10
testing8
Programming languages (5)
Github contributions (5)
galaxyproject/galaxy
Aug 2022 - Dec 2022
Data intensive science for everyone.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 reviews, 6 commits, 2 PRs in 4 months
Contributions summary:Gulsum primarily focused on integrating CUDA and GPU resource management within the Galaxy project. Their contributions involved adding CUDA-related requirements, enumerations, and corresponding test extensions to the tool configuration and dependency files. They modified core files to incorporate these GPU-related functionalities, then reverted some changes, indicating an iterative development process. These updates enabled the system to manage and schedule tasks utilizing GPU resources.
pythonsciencepipelinednadata-science
gulsumgudukbay/galaxy
Aug 2020 - Dec 2022
Data intensive science for everyone.
Contributions:2 PRs, 43 pushes, 1 branch in 2 years 3 months
intensivepythonsciencedata-science
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