Princeton NextG Faculty Spotlight Series Presentation

Featured Faculty: Professor Vincent Poor.
Date
Mar 19, 2024, 12:00 pm1:00 pm
Location
Zoom

Speaker

Details

Event Description

Please join us for a Princeton NextG Faculty Spotlight Series Presentation feat. Professor Vincent Poor.

Registration is required – please register in advance for this meeting: After registering, you will receive a confirmation email containing information about joining the meeting

Biography: H. Vincent Poor is the Michael Henry Strater University Professor at Princeton University, where his interests include information theory, machine learning and network science, and their applications in wireless networks, energy systems, and related areas. Among his publications in these areas is the recent book Machine Learning and Wireless Communications, published by Cambridge University Press. Dr. Poor is a member of the U.S. National Academy of Engineering and the U.S. National Academy of Sciences and is a foreign member of the Royal Society, and other national and international academies. He received the IEEE Alexander Graham Bell Medal in 2017, and holds honorary doctorates and professorships from a number of universities in Asia, Europe and North America. https://ece.princeton.edu/people/h-vincent-poor

This is a virtual event. Zoom link below.

https://princeton.zoom.us/meeting/register/tJEtf-CvrD8uGtO1P3elA3MzJptLjRJ_dj6T

Professor Poor will present his research, followed by a Q&A/discussion period.

The NextG Faculty Spotlight Series is hosted by Princeton NextG, an initiative of Princeton's School of Engineering and Applied Sciences. The NextG Initiative at Princeton is creating the foundation for intelligent networks of the future across wireless, backbone networking, and cloud systems. The initiative focuses on cross-disciplinary approaches, bringing theory to practice, and covering the ‘full stack’ from the underlying technological fabric in integrated electronic and photonic circuits and systems, edge networks, IOT and cloud, to foundational theory, algorithms and AI approaches that make these networks scalable, efficient, secure, and accessible.