Michael Luk


  • Leadership
  • Technology


  • Artificial Intelligence
  • Production AI
  • Research & Development

Michael Luk, PhD

Co-Founder & Chief Technology Officer

Michael Luk

about Michael

Dr. Michael Luk, Ph.D., is the Co-Founder and Chief Technology Officer of SFL Scientific. Michael is an industry advisor at Brown University and a CTO advisor to S&P 500 organizations. He studied theoretical physics at Imperial College London, Mathematics at the University of Cambridge, and earned his Ph.D. as an experimental participle physicist at Brown University working at CERN, leading to the discovery of the Higgs Boson. His research included both analytical and algorithmic components and he gained extensive enterprise data science experience at Intel, developing yield forecasting, anomaly detection, and automation systems for their technology division.

Dr. Luk has worked in technical consulting and AI professional services, becoming a recognized expert in developing AI pipelines, machine vision models, and natural language processing solutions, having developed and managed production systems as the backbone of business operations for start-ups to multi-billion dollar organizations. As the Co-Founder of SFL Scientific, Dr. Luk leads the data science organization to address the full lifecycle of artificial intelligence solution development, from data strategy and engineering to scaling solutions through cloud, HPC, and edge devices. He has been involved in over one hundred custom AI initiatives and projects for the public, federal, and private organizations, and was responsible for objectives, proposed algorithmic approaches, implementation, budget, and execution. Michael has provided organizations with innovative, practical solutions by improving operations and integrating emerging technology through the development of novel data-driven systems and continues to engineer frameworks to deliver faster, more efficient, and cost-effective technologies to solve complex problems across text, time-series, and image data.

Michael is an expert in data analysis, electronics, mathematical sciences, and is fluent in English, Cantonese, and French. His current interests lie in tackling a wide range of NLP and Artificial Intelligence projects leveraging HPC and GPU-accelerated methods.