Peter Ramadge
Gordon Y.S. Wu Professor of Engineering
Professor of Electrical Engineering
Office:
B212
E-Quad
Princeton,
NJ
08544
Phone: 609-258-4645
Interdisciplinary Research Area: Applied Math, Bioengineering, Data Science
Research Area: Video and image processing; adaptive systems; adaptive signal processing; adaptive control; discrete-event systems, optimization of queueing systems; video analysis, annotation and search
Areas of Impact
Bioengineering and Health
Bioengineers at Princeton bring together fundamental questions about how living systems work with an engineering approach to solving problems. While much work in bioengineering aims to improve human health, advances in the field also help address other global challenges, such as sustainable food, energy, water, and materials.
Data Science
Data science accelerates discovery across nearly all areas of science, engineering, and social science. Students and faculty in this area create new data-analysis techniques and harness advanced computing and storage systems to solve problems in biology, the environment, materials science, communications, security, transportation, and many other areas.
Robotics and Cyberphysical Systems
The use of robots is moving rapidly beyond controlled environments such as factories to complex environments in the midst of human activity, demanding a nimble cross-disciplinary approach. Princeton engineers are advancing the productive, safe, and ethical use of robotics in society by building and connecting expertise in sensing, artificial intelligence, neuroscience, public policy, and other fields.
Primary affiliation
Electrical Engineering
Princeton’s electrical engineering program, started in 1889 as one of the first in the United States, remains at the forefront of the field, with research aimed at improving human health, energy and environmental systems, computing and communications, and security. Specific areas of research include the physics of semiconductors; electronic and optical devices; the design of computers and networks; materials science and nanotechnologies; algorithms and structures for information; and biological technologies.
