Summary
Muhammad Tabassum is an Agile Product Owner and AI/ML engineer with eight years of experience bridging academic research and industrial product delivery, currently leading release planning and productization of deep-learning PHY solutions for 6G at Nokia in Espoo. He combines a PhD in Signal Processing and Data Science with hands-on SDLC experience across SoC-based and cloud RAN products, previously managing a ~20-person Scrum team and contributing to quality and learning streams. His research background includes novel sparse and compressibility-driven supervised learning methods for genomics and complex-valued regularization solvers, plus published algorithms such as a B-positive particle swarm optimizer. Comfortable moving between MATLAB/R research prototypes and production ML pipelines, he has a track record of accelerating project outcomes through clear technical direction and pedagogy-informed mentoring. Notably, he has repeatedly turned high-dimensional signal and genomic problems into computationally efficient solutions that minimize features and compute while improving accuracy.
8 years of coding experience
9 years of employment as a software developer
Doctor of Science (Tech.) | Ph.D. Signal Processing and Data Science, Doctor of Science (Tech.) | Ph.D. Signal Processing and Data Science at Aalto University
Master of Science (M.Sc.) Electrical Engineering (Communications), Master of Science (M.Sc.) Electrical Engineering (Communications) at King Saud University
Bachelor of Science (BS) Telecommunication Engineering, Bachelor of Science (BS) Telecommunication Engineering at National University of Computer and Emerging Sciences
Finnish, Arabic, Punjabi, Urdu, English