Suggestions
Garrett van Ryzin
VP/Distinguished Scientist, Supply Chain Optimization Technology (SCOT) at Amazon; Paul M. Montrone Professor Emeritus, Columbia Business School
Garrett van Ryzin is a prominent figure in the fields of operations research and technology management, currently serving as the Vice President and Distinguished Scientist at Amazon, specifically within the Supply Chain Optimization Technologies (SCOT) organization. He joined Amazon in August 2020 and has since focused on innovations in inventory management and last-mile delivery optimization.1
Educational Background
- Bachelor of Science (BS) in Electrical Engineering from Columbia University (1982-1985)
- Master of Science (MS) in Electrical Engineering and Computer Science from MIT (1985-1987)
- Doctor of Philosophy (Ph.D.) in Operations Research from MIT (1987-1991)
Career Highlights
- Amazon: VP/Distinguished Scientist since August 2020, focusing on enhancing supply chain efficiency.
- Lyft: Distinguished Scientist and Head of Marketplace Labs (2017-2020), where he led R&D to improve marketplace experiences.
- Cornell Tech: Dyson Family Professor of Operations, Technology, and Information Management (2017-2020).
- Uber: Head of Marketplace Optimization Advanced Development (2015-2017), developing models for driver dispatch and pricing.
- Columbia University: Paul M. Montrone Professor Emeritus in Decision Risk and Operations, with a tenure from 1991 to 2017.
Research Contributions
Van Ryzin's research has significantly impacted various sectors, particularly in revenue management and operational efficiency. His work includes developing algorithms for dynamic pricing and demand modeling, which have been utilized by airlines and retail companies to optimize pricing strategies and inventory management.12
Personal Insights
Van Ryzin has expressed admiration for Amazon's innovative culture and long-term strategic vision, which aligns with his scientific approach to problem-solving. He emphasizes the importance of collaboration among different optimization models to enhance overall system performance.1