Maruan Al-shedivat
Senior Director, Machine Learning Research at Genesis Molecular AI
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolMaruan Al-shedivat is Head of Machine Learning Research at Genesis Molecular AI with 13 years of experience building probabilistic and deep learning systems for life sciences and engineering applications. He combines academic rigor from a PhD in AI at Carnegie Mellon with hands-on product and engineering leadership—spanning roles from OpenAI research to founding a startup that automated blood microscopy and piloted in hospitals. His research focuses on probabilistic modeling, multi-task learning, adaptation, personalization, and interpretable models, and he has contributed to federated learning tooling at Google Research by implementing FedPA-compatible components. Equally comfortable shipping production-quality code, he’s an active open-source contributor (e.g., enhancing the popular al-folio academic Jekyll theme with KaTeX and modular refactors). Based in New York, he brings a rare blend of theoretical depth and practical systems engineering to scale reliable, data-driven products.
13 years of coding experience
15 years of employment as a software developer
Master of Science (M.Sc.) Computer Science AI, Master of Science (M.Sc.) Computer Science AI at KAUST (King Abdullah University of Science and Technology)Lomonosov Moscow State UniversityDoctor of Philosophy (Ph.D.) Artificial Intelligence, Doctor of Philosophy (Ph.D.) Artificial Intelligence at Carnegie Mellon UniversityMaster's degree Computer Science, Master's degree Computer Science at Yandex School of Data Analysis
English, Russian, Arabic
Github Skills (13)
css10
algorithms10
machine-learning10
tensorflow10
federated-learning10
jekyll10
python10
jekyll-theme10
optimization9
javascript9
katex9
website-design7
academia7
Programming languages (12)
Github contributions (5)
alshedivat/al-folio
Dec 2022 - Dec 2022
A beautiful, simple, clean, and responsive Jekyll theme for academics
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:24 releases, 173 reviews, 4 commits in 9 days
Contributions summary:Maruan contributed to the `al-folio` project by implementing and integrating math support using KaTeX, enhancing the theme's capabilities for academic content. They also refactored the theme's structure by extracting social and news sections into separate includes, improving modularity. Further contributions involved adding a profile property to the about page layout and restructuring asset management, as well as updating the theme with a publications page.
responsive-jekyll-themeacademicscleanjekylljekyll-theme
google-research/federated
Mar 2021 - Apr 2021
A collection of Google research projects related to Federated Learning and Federated Analytics.
Role in this project:ML Engineer
ML EngineerContributions:2 reviews, 7 commits, 1 PR in 12 days
Contributions summary:Maruan contributed to the implementation and refinement of the Federated Posterior Averaging (FedPA) algorithm within the repository. Their work included adding core functionalities, making the code compatible with the latest TensorFlow Federated (TFF) nightly, and fixing potential edge cases. The user focused on the client-side updates, delta calculations, and integrating these components within the broader federated learning framework.
analyticsfederated-analyticsmachine-learningkubernetesfederated-learning
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