Radio Analytics: The Future Platform for Wireless Positioning, Tracking and Sensing (IST, DEEC and INESC-ID Distinguished Lecture)
On May 11th, at 11am, INESC-ID will promote the 11th session of IST Distinguished Lecture Series entitled “Radio Analytics: The Future Platform for Wireless Positioning, Tracking and Sensing”. The lecture will be given by Professor K. J. Ray Liu, Distinguished Scholar-Teacher of the University of Maryland, and IEEE Vice-President, Technical Activities – Elect, and will discuss the future of smart radios for smart life.
Prof. K. J. Ray Liu,
Electrical and Computer Engineering Department,
University of Maryland, College Park
What smart impact will future 5G and IoT bring to our lives? Many may wonder, and even speculate, but do we really know? With more and more bandwidth readily available for the next generation of wireless applications, many more smart applications/services unimaginable today may be possible. In this talk, we will show that with more bandwidth, one can see many multi-paths, which can serve as hundreds of virtual antennas that can be leveraged as new degrees of freedom for smart life. Together with the fundamental physical principle of time reversal to focus energy to some specific positions and the use of machine learning, a revolutionary radio analytic platform can be built to enable many cutting-edge IoT applications that have been envisioned for a long time, but have never been achieved.
We will show the world’s first ever centimeter-accuracy wireless indoor positioning systems that can offer indoor GPS-like capability to track human or any indoor objects without any infrastructure, as long as WiFi or LTE is available. Such a technology forms the core of a smart radios platform that can be applied to home/office monitoring/security, radio human biometrics, vital signs detection, wireless charging, and 5G communications. In essence, in the future of wireless world, communication, as we see it, will be just a small component of what’s possible. There are many more magic-like smart applications that can be made possible, allowing us to decipher our surrounding world with a new “sixth sense”. Some demo videos will be shown to illustrate the future of smart radios for smart life.
Dr. K. J. Ray Liu was named a Distinguished Scholar-Teacher of University of Maryland, College Park, in 2007, where he is Christine Kim Eminent Professor of Information Technology. He is the founder of Origin Wireless, Inc., a high-tech start-up developing smart radios for smart life. Dr. Liu was a recipient of the 2016 IEEE Leon K. Kirchmayer Award on graduate teaching and mentoring, IEEE Signal Processing Society 2014 Society Award for “influential technical contributions and profound leadership impact”, IEEE Signal Processing Society 2009 Technical Achievement Award, and more than a dozen best paper awards. Recognized by Web of Science as a Highly Cited Researcher, he is a Fellow of IEEE and AAAS.
Dr. Liu is IEEE Vice President, Technical Activities – Elect, He was Division IX Director of IEEE Board of Director, President of IEEE Signal Processing Society, where he has served as Vice President – Publications and Editor-in-Chief of IEEE Signal Processing Magazine. He also received teaching and research recognitions from University of Maryland including university-level Invention of the Year Award (three times), and college-level Poole and Kent Senior Faculty Teaching Award, Outstanding Faculty Research Award, and Outstanding Faculty Service Award, all from A. James Clark School of Engineering (each award honors one faculty per year from the entire college).
Isabel Maria Martins Trancoso
Anfiteatro Abreu Faro, IST
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series takes place until July 16, between 17:30 and 18:30, via Zoom.
The seminars aims to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goals of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information and the next seminars available here.
LxMLS 2020 – 10th Lisbon Machine Learning School
The 10th edition of Lisbon Machine Learning School, LxMLS, will take place from July 21st to July 29th at Instituto Superior Técnico (IST).
This event is organized by IST, Instituto de Telecomunicações (IT), INESC-ID, Unbabel, and Priberam Labs.
Applications until March 15th. For more information and to apply, access here.