Susik Yoon
Susik Yoon (윤수식, 尹秀植) | susikyoon{@}kaist{.}ac{.}kr | Github | LinkedIn | CV
Research interest: Outlier(anomaly) detection, Online learning, Data stream mining, Complex event processing
Doctoral dissertation: Accelerating Similarity- and Model-based Outlier Detection from a Data Stream
Master's thesis: Load Balancing for Distributed Processing of Spatial Data Stream
Education
2017.03 - 2021.02 PhD, Data Mining Lab (Prof. Jae-Gil Lee), Graduate School of Knowledge Service Engineering, KAIST
2015.03 - 2017.02 Master, Data Mining Lab (Prof. Jae-Gil Lee), Graduate School of Knowledge Service Engineering, KAIST
2008.02 - 2015.02 Bachelor, Industrial and Systems Engineering/Business and Technology Management, KAIST
2006.02 - 2008.02 Daegu Science High School
Selected Publications (full list)
Yoon, S., Shin Y., Lee, J., and Lee, B. S., Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries, In Proc. 2021 ACM Int'l Conf. on Management of Data (SIGMOD), June 2021. (To appear)
Yoon, S., Lee, J., and Lee, B. S., Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping, In Proc. 26th Int'l Conf. on Knowledge Discovery and Data Mining (KDD), Aug. 2020. (Top conference, acceptance rate: 16.9%) [Paper][Slide][Poster][Code][Video(full/poster/promotion)]
Yoon, S., Lee, J., and Lee, B. S., NETS: Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing, In Proc. 40th Int'l Conf. on Very Large Data Bases (VLDB) / Proc. of The VLDB Endowment (PVLDB), Aug. 2019. (Top conference, acceptance rate: 18.9%) [Paper][Slide][Poster][Code][Video]
Professional Experiences
2014.06 - 2014.08 Trainee, i2, Danish E-infrastructure Cooperation
2013.06 - 2013.12 IT Intern, Infrastructure and Shared Services, General Electric Korea
2010.06 - 2012.04 Computer Emergency Response Team, Defense Security Command, Ministry of National Defense
2010.02 - 2010.05 Research Assistant, Nemo Partners Strategy Consulting Group
Research Projects
2018.07 - Current Machine Learning Technology for Real-Time Anomaly Detection in Semiconductor Processes, Samsung Electronics Co., Ltd
2017.11 - Current Evolutionary Self-Learning for Multivariate Stream Big Data in Smart Factories, National Research Foundation of Korea
2015.04 - 2020.02 Geospatial Big Data Management, Analysis and Service Platform Technology Development, Korea Agency for Infrastructure Technology Advancement/Ministry of Land, Infrastructure and Transport
Teaching Experiences
Teaching Assistant of KSE525: Data Mining and Knowledge Discovery in 2017 Spring, 2018 Spring, 2019 Spring
Teaching Assistant of Undergraduate Research Program in 2017 Summer/Fall
Talks
2020.12. Invited Paper Presentation, Korea Software Congress 2020
2020.12. NAVER Techtalk
2019.12. Invited Paper Presentation, Korea Software Congress 2019
Awards
2021.01. Best Presentation Award, The Biannual KSE PhD Student Open Presentation
2020.07. Best Paper Award, Strategic Collaboration Academic Program, Samsung Electronics
2019.12. Best Presentation Award, The Biannual KSE Student Colloquium
2017.06. Best Paper Award, Korea Computing Congress 2017