Phil Kaminsky is Executive Associate Dean and Associate Dean for Student Affairs in the UC Berkeley College of Engineering, and Earl J. Isaac Professor in the Science and Analysis of Decision Making in the Department of Industrial Engineering and Operations Research at UC Berkeley, where he previously served as the faculty director of the Sutardja Center for Entrepreneurship and Technology, director of the Initiative for Research in Biopharmaceutical Operations, and department chair of Industrial Engineering and Operations Research.
Professor Kaminsky's research focuses primarily on the analysis and development of robust and efficient tools and techniques for design, operation, and risk management in logistics systems and supply chains. This encompasses operational issues including the modeling and analysis of production and control systems, as well as more tactical and strategic concerns, including the integration of production, distribution, and pricing strategies, and more broadly the analysis of issues that arise in integrated supply chain management.
Much of his current work is centered on two main themes: strategic, tactical, and operational issues that arise in the operation of biopharmaceutical firms; and collaborative, sustainable logistics. Other current projects focus on the development of novel flexible algorithms for supply chain optimization, container terminal operations, efficient operation of operating rooms, and quantitative modeling of behavior change for personalized healthcare. His research has been funded by the National Science Foundation, BioMarin, Bayer, Genentech, Navis, Project Production Institute, Material Handling Institute, Toyota, and FICO.
Professor Kaminsky received his BS in Chemical Engineering from Columbia University in 1989, and his MS and PhD in Industrial Engineering and Management Science from Northwestern University in 1997. Before graduate school, he worked in production engineering and control at Merck in Rahway, New Jersey.
- Analysis of integrated supply chain management models
- Logistics Collaboration
- Healthcare operations
- Production scheduling
- Modeling and analysis of production control and logistics
- Systems, design and analysis of algorithms
- Integration of production and distribution strategies
See personal web page.