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[세미나] [데이터사이언스 대학원] Data Science, Artificial Intelligence, and Information Theory : Advice to Future “Students”

2020.03.30.l 조회수 4510
연사 : Young-Han Kim, Professor, University of California San Diego
일시 : 2020-03-31 17:00 ~ 18:00
장소 : Zoom 화상 세미나 (http://gsds.snu.ac.kr/에 주소 게재예정)

데이터사이언스 세미나 특강


Data Science, Artificial Intelligence, and Information Theory

: Advice to Future “Students”


연사:  Young-Han Kim, Professor, University of California San Diego

일시: 2020년 3월 31일(화), 17:00 ~ 18:00

장소: Zoom 화상 세미나 (http://gsds.snu.ac.kr/에 주소 게재예정)



Abstract:


Data science is a multi-faceted area, the history of which traces back to the dawn of modern science and the future of which relies on a stable marriage between statistics and computing. As an information theorist, industrial engineer, and data scientist, I will discuss a few key lessons for fledgling data scientists, quoting the giants in the field and reflecting on my own journey. Along the way, I will also present a biased introduction to artificial intelligence and information theory --- two cousins of data science that are often misunderstood and under understood, respectively. There is no prerequisite to this talk other than general intelligence.

 

Biography:


Young-Han Kim received his B.S. degree in Electrical Engineering from Seoul National University in 1996 and his Ph.D. degree in Electrical Engineering (M.S. degrees in Statistics and in Electrical Engineering) from Stanford University in 2006. Since then he has been on the faculty of the Department of Electrical and Computer Engineering and the Halicioglu Data Science Institute at the University of California, San Diego, where he is a Professor. He is currently on sabbatical leave from UCSD, visiting SK Hynix as a Fellow. His research interests include information theory, signal processing, machine learning, data science, mathematical engineering, and their applications in science and engineering (communications, networking, cryptography, microelectronics, semiconductor manufacturing, and bioinformatics). He has coauthored a highly cited textbook ``Network Information Theory'' (Cambridge University Press, 2011) and a recent monograph ``Fundamentals of Index Coding'' (Now Publishers, 2018). He has received several awards and honors for his contributions, including the NSF CAREER Award (2008), the US-Israel BSF Bergmann Memorial Award (2009), the IEEE Information Theory Paper Award (2012), and the first IEEE James L. Massey Research and Teaching Award (2015). He is a fellow of the IEEE.

담당교수: 데이터사이언스대학원 차상균 / 문의: 02) 880-1331 / 조교 천준하 (jhchun@kdb.snu.ac.kr) 



                 서울대학교 데이터사이언스대학원

                     Graduate School of Data Science