Keynote Speeches

April 14, 2021 11:10 ~ 11:50
Keynote Speech I (Prof. Jong-Seon No, Seoul National University, Korea)
Privacy-Preserving Machine Learning Over Encrypted Data

Abstract
The recent development of cloud computing and machine learning raises a privacy problem; how can one outsource computation in machine learning for confidential data? Fully homomorphic encryption (FHE) is a specific class of public key encryption schemes that allows computation over encrypted data. However, due to the limited data types and the number of supported operations of FHE, it is not straightforward to implement machine learning algorithms based on FHE.
In this talk, the following aspects of privacy-preserving machine learning (PPML) based on FHE will be introduced: (a) Comparison of FHE and machine learning operations in the aspect of priority and efficiency. (b) How to apply homomorphic operations and its packing method to machine learning algorithms through approximation and other modifications. (c) The-state-of-art research trends and results of PPML based on FHE.

Biography
Jong-Seon No received the B.S. and M.S.E.E. degrees in electronics engineering from Seoul National University, Seoul, Korea, in 1981 and 1984, respectively, and the Ph.D. degree in electrical engineering from the University of Southern California, Los Angeles, CA, USA, in 1988. He was a Senior MTS with Hughes Network Systems from 1988 to 1990. He joined the faculty of the Department of Electrical and Computer Engineering, Seoul National University, in 1999, where he is currently a Professor. He became an IEEE Fellow through the IEEE Information Theory Society in 2012. He was a recipient of the IEEE Information Theory Society Chapter of the Year Award in 2007. From 1996 to 2008, he served as a Founding Chair of the Seoul Chapter of the IEEE Information Theory Society. He served as a General Co-Chair of the International Symposium on Information Theory and Its Applications 2006 (ISITA2006) and the International Symposium on Information Theory 2009 (ISIT2009), Seoul. He became a Member of the National Academy of Engineering of Korea (NAEK), 2015, where he served as a Division Chair of Electrical, Electronic, and Information Engineering from 2019 to 2020. His area of research interests includes cryptography, machine learning, error-correcting codes (ECC), ECC for memory devices, sequences, interference alignment, and wireless communication systems.

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April 14, 2021 11:50 ~ 12:30
Keynote Speech II (Prof. Lingyang Song, Peking University, China)
MetaEverything: Intelligent MetaMaterial aided Sensing and Communications

Abstract
Intelligent MetaMaterial recently stands out as a novel approach to improve the quality of communication links. The talk will provide the state-of-the-art of research on meta-surface assisted sensing and communications from the perspectives of physical, MAC, network, and application layers. It focuses on two main types of meta-surface based applications, i.e., cellular communications and RF sensing. It will discuss the meta-surface hardware design as well as machine learning techniques for different sensing applications. Technical issues related to communications will also be addressed including beamforming scheme design, phase shift optimization, and MAC layer protocol design.

Biography
Lingyang Song received his PhD from the University of York, UK, in 2007, where he received the K. M. Stott Prize for excellent research. He worked as a research fellow at the University of Oslo, Norway until rejoining Philips Research UK in March 2008. In May 2009, he joined the School of Electronics Engineering and Computer Science, Peking University, and is now a Boya Distinguished Professor. He is the co-author of a number of best paper awards, including IEEE ComSoc Leonard G. Abraham Prize in 2016, IEEE ICC 2014, IEEE ICC 2015, IEEE Globecom 2014. He has served as a Distinguished Lecturer of IEEE Communications Society, an Area Editor of IEEE Transactions on Vehicular Technology, an Editor of IEEE Transactions on Communications. He is a Fellow of IEEE, and a Clarivate Analytics Highly Cited Researcher in 2018.

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April 15, 2021 16:20 – 17:00
Keynote Speech III (Dr. Seung Chan Bang, SVP, ETRI, Korea)
ETRI Communications and Media Technologies for x+AI

Abstract
First, ETRI x+AI strategies are introduced. Communications and Media/Content technologies are being combined with AI for better performance. Regarding several technologies such as adaptive waveform for THz, distributed network for AI, radar target classification by AI, video compression by AI, AI based 3D character generation, etc, their backgrounds, methods of combining AI, and some results are explained.

Biography

• SVP of ETRI, Head of Telecommunications and Media Research Lab.
• Former member of Gold Star and Digicom Research Institute
• B.S.(1984), M.S.(1986), and Ph.D(1994). in Electronics Engineering from Seoul National University