Full Radio Spectrum Awareness Using Machine Learning and Deep Learning
The Department of Electrical & Computer Engineering at Concordia University, the IEEE Montreal Society Chapters of Circuits & Systems and Communications, and Regroupement Stratégique en Microsystèmes du Québec are inviting all interested IEEE Montreal members and other engineers and students to a technical seminar on:
“Full Radio Spectrum Awareness Using Machine Learning and Deep Learning”
Who: Dr. Yu-Dong Yao, Dept. of Electrical & Computer Engineering, Stevens Institute of Technology, New Jersey
When: Tuesday September 4, 2018, 18:00 – 19:30
Where: Room EV 2.184, EV Building, Concordia University, 1515 Ste. Catherine West
For info: please contact Dr. Wei-Ping Zhu at weiping@ece.concordia.ca
Abstract
Deep learning (DL) is a new machine learning (ML) methodology that has found successful implementations in many application domains. This presentation discusses research results in the use of ML and DL in radio spectrum activity identification, modulation classification, medium access protocol classification, and wireless service identification.
Short Bio
Dr. Yu-Dong Yao has been a professor at Stevens Institute of Technology, New Jersey, since 2000. He served as a department chair of electrical and computer engineering from 2007 to 2018. He is currently a director of Stevens’ Wireless Information Systems Engineering Laboratory (WISELAB). Dr. Yao was with Carleton University (Ottawa) and Spar Aerospace (Montreal) from 1987 to 1994. His research interests include wireless communications, cognitive radio, machine learning, and deep learning. He holds thirteen U.S. patents. He was elected a Fellow of IEEE (2011), National Academy of Inventors (2015), and Canadian Academy of Engineering (2017).