Kaoutar Maghraoui
Principal Research Scientist And Manager, IBM Research AI Platforms, AI Hardware Center
Town of Somers, New York, United States
Summary
👤
Senior🎓
Top SchoolKaoutar Maghraoui is a Principal Research Scientist and manager at IBM Research AI Platforms, leading the AI Hardware Center’s end-user testbed and driving hardware–software co-design for next-generation AI accelerators. With a PhD from Rensselaer and over two decades of research and teaching experience, she blends deep systems expertise—performance optimization, distributed ML, CUDA and PyTorch—with practical AI engineering to boost real-world model efficiency. She also teaches High Performance Machine Learning at Columbia, bringing course material from MPI and ring reductions to quantization and model compression into the classroom. An active contributor to IBM’s open-source Analog Hardware Acceleration Kit documentation, she focuses on making complex tooling accessible to developers. Recognized with IBM eminence awards and ACM distinction, she is committed to advancing AI infrastructure while mentoring the next generation and increasing women’s participation in STEM.
8 years of coding experience
6 years of employment as a software developer
Ph.D Computer Science, Ph.D Computer Science at Rensselaer Polytechnic InstituteMasters Bachelor Computer Science, Masters Bachelor Computer Science at Al Akhawayn University
English, French, Arabic
Github Skills (6)
documentation10
jupyter-notebook9
python5
ai5
neural-network5
pytorch5
Programming languages (4)
Github contributions (5)
IBM/aihwkit
Aug 2021 - Jan 2023
IBM Analog Hardware Acceleration Kit
Role in this project:
Technical Writer
Technical WriterContributions:5 releases, 91 reviews, 13 commits in 1 year 5 months
Contributions summary:Kaoutar primarily contributed documentation and examples within the repository. Their work includes adding notebooks, creating example files, and updating existing documentation, including API documentation. They also updated the changelog and added instructions on running the examples. This indicates a focus on making the project more accessible and easier to understand for other developers.
cudapytorchaccelerationneural-networksmachine-learning
IBM-AI-Hardware-Center/aihwkit-notebooks
Nov 2021 - May 2022
Notebooks for the Analog AI Hardware Accelerator toolkit
Contributions:7 PRs, 22 pushes, 2 branches in 5 months
tvmmachine-learningainotebookshardware
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.