연사: 문태섭, 서울대학교 전기·정보공학부 교수

일시: 2021년 03월 04일(목), 17:00 ~ 18:00

장소: 화상강의

Abstract:
In this talk, I will first briefly introduce my professional journey after graduating from and before joining SNU EE. Then, I will summarize my research endeavors on how I tried to pursue three different facets of research, i.e., theory, algorithm, and applications, in the area of big data and machine (deep) learning, throughout the course of my journey. More specifically, for theoretical research, I will show how regret minimization framework can be utilized to rigorously analyze the performance of denoising methods. Regarding algorithm research, I will present three principles - scalability, adaptivity, and stability - that I considered in devising new algorithms in several different areas, such as web search ranking, continual learning, and explainable AI. As examples of applications research, I will sample some of my work from interdisciplinary data science projects on air quality monitoring and radar signal processing. Finally, I will conclude the talk with my future research and teaching plans.

Biography:

l 학력

2008 (박사)	Department of Electrical Engineering, Stanford University
2004 (석사)	Department of Electrical Engineering, Stanford University
2002 (학사)	Department of Electrical Engineering, 서울대학교

l 경력

2021 ~ 현재	Associate Professor, Department of Electrical and Computer Engineering, 서울대학교
2017 ~ 2021	Assistant/Associate Professor, Department of Electrical and Computer Engineering, 성균관대학교
2015 ~ 2017	Assistant Professor, Department of ICE, 대구경북과학기술원
2013 ~ 2015	Research Staff Member, 삼성전자 종합기술원
2012 ~ 2013	Postdoctoral Researcher, Department of Statistics, UC Berkeley
2008 ~ 2012	Scientist, Yahoo! Labs

담당교수: 전기·정보공학부 박세웅 / 문의: 양진모(jmyang@netlab.snu.ac.kr)