About

Rouzbeh Shirvani is a highly skilled Machine Learning Architect with a passion for working on futuristic ideas, particularly in the context of startups. With a strong academic background in Computer Science, Electrical Engineering, and Physics, Rouzbeh has a PhD in Electrical Engineering and Computer Science from Howard University, as well as a Master of Science in Electrical and Electronics Engineering from Sharif University of Technology and a Bachelor of Science in Electrical and Electronics Engineering from Iran University of Science and Technology. After completing his PhD, Rouzbeh chose to work in the startup world, declining offers from big corporations like Adobe, Microsoft, and Qualcomm. He enjoys working on ideas that stretch him beyond his comfort zone and has a preference for David over Goliath in the fight between the two. In his previous role at Athelas, Rouzbeh led the efforts in platelet monitoring devices, developing machine learning models, designing electrical circuit boards, writing software stacks, and working with regulatory bodies like FDA. Currently, Rouzbeh is a Machine Learning Architect at Syntiant, where he is responsible for bringing new machine learning capabilities to Syntiant's neural decision processors. He works with other stakeholders to find solutions to their unique machine learning problems and writes the ML software that the chip needs to run trained models. Rouzbeh's technical skills include ML, Senior Software Engineer, and Software Engineer, and he has almost four years of relevant experience. With a strong academic background and experience in both industry and startups, Rouzbeh is a valuable asset to any team.