Summary
Samir Moustafa is a Data Scientist and researcher based in Vienna with eight years of experience building and deploying production-ready AI solutions that bridge cutting-edge research and real-world systems. He has a strong track record in neural network quantization, compression and model-efficiency techniques—delivering practical speedups (e.g., 5× inference reduction) and memory reductions (up to 11×) validated in published work. Samir has shipped optimizations at Huawei integrated with chipset tooling and mobile runtime feedback, and later led impactful research projects at the University of Vienna on GNN expressivity, robustness, and efficient architectures. As a lecturer he translates theory into practice, teaching numerical algorithms and high-performance computational tools while supervising theses on preconditioning and efficient GNNs. Now at CeMM, he applies HPC and advanced imaging workflows to pathology, combining domain knowledge with applied ML engineering. His profile blends systems-level deployment experience with formal contributions to AutoML, computer vision, and security-aware model design—an unusual mix that accelerates research into usable products.
8 years of coding experience
2 years of employment as a software developer
Nanodegree Deep Learning, Nanodegree Deep Learning at Udacity
Training Cross Platform, Training Cross Platform at Information Technology Institute (ITI)
Bachelor of Science - BSc. Computer Science, Bachelor of Science - BSc. Computer Science at Alexandria University
Master's degree Data Science, Master's degree Data Science at Skolkovo Institute of Science and Technology
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Vienna
English, Arabic