Notice

 
Abstract
In recent years, machine learning is expanding its application to signal processing, such as wireless communications, radar signal processing, and etc, hopefully leading us to success of the 4th industrial revolution. Evolution of modern signal processing has been made by optimization techniques, sometimes based on understanding probabilistic phenomenon. In this talk, a brief overview of machine learning techniques is given, which can be applied to modern signal processing. Then, a few applications and research challenges are introduced. In-depth discussion on building and operating start-up companies is provided.
 
Speaker biography
Dr. Hyun Jong Yang received the B.S. degree in electrical engineering from Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, in 2004, and the M.S. and Ph.D. degrees in electrical engineering from KAIST, in 2006 and 2010, respectively. From Aug. 2010 to Aug. 2011, he was a research fellow at Korea Institute Ocean Science Technology (KIOST), Daejoen, Republic of Korea. From Oct. 2011 to Oct. 2012, he worked as a post-doctoral researcher in the Electrical Engineering Department, Stanford University, Stanford, CA. From Oct. 2012 to Aug. 2013, he was a Staff II Systems Design Engineer, Broadcom Corporation, Sunnyvale, CA, where he developed physical-layer algorithms for LTE-A MIMO receivers. In addition, he was a delegate of Broadcom in 3GPP standard meetings for RAN1 Rel-12 technologies. Since Aug. 2013, he has been an Assistant Professor in the School of Electrical and Computer Engineering, UNIST, Ulsan, Korea. His fields of interests are algorithms and theory for wireless communication and their applications and implementation. He is a co-founder and CEO of EgoVid Inc, a research-oriented start-up company studying privacy-preserving machine learning.