Learn about the Andlinger Center for Energy and the Environment and its mission, hear from our director, read the latest in news from the center, explore our building and its facilities, check out our events calendar, and discover other programs and activities happening within the center.
Meet our leadership team, staff, jointly appointed faculty members, research scholars, visiting faculty, and postdoctoral research associates. Other key constituents at the center include members of our External Advisory Committee and Executive Committee, as well as associated faculty members.
Browse our research directory to learn about the expertise of our faculty. View abstracts of Andlinger-funded research. Learn about funding opportunities for research projects.
Discover the many courses on energy and environmental issues that Princeton University and the Andlinger Center for Energy and the Environment have to offer. Enroll in our certificate programs and apply for special student opportunities, such as internships, fellowships, and research funding.
Rapid Switch is a solutions-focused, international research effort led by the Andlinger Center for the Energy and the Environment that aims to identify a realistic pace and pathways for decarbonizing the world, sector by sector, and region by region.
Energy Technology Distillates is a series of publications that provide succinct yet substantive information about emerging topics in energy and the environment. Geared for policymakers, educators, students, and interested citizens, the briefings combine technological, economic, and policy considerations.
Princeton E-ffiliates Partnership, a membership-based program, offers corporations a unique opportunity to engage in big-picture thinking and to find innovative solutions in energy and the environment. Member companies engage in close collaborations with academic experts to pursue transformational innovations.
Professor of Operations Research and Financial Engineering
Andlinger Center Associated Faculty
209 Sherrerd Hall
Statistical modeling to examine evidence for global warming in local weather data