I am a postdoctoral researcher in the Department of Computer Science at UIUC, working with Prof. Jiawei Han. I obtained my Ph.D. degree at KAIST under the supervision of Prof. Jae-Gil Lee. My research interests cover a wide range of topics in data mining and machine learning. Specifically, I am interested in learning and mining knowledge from unstructured and evolving data streams.

Email: susik{@}illinois{.}edu | Google Scholar | Github | LinkedIn | CV (last update: May 19th, 2022)

Recent Publications (full list)

  • Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream (KDD22)

    • Susik Yoon, Youngjun Lee, Jae-Gil Lee, Byung Suk Lee | To appear

  • Coherence-based Label Propagation over Time Series for Accelerated Active Learning (ICLR22)

    • Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee | [Paper][Code]

  • TaxoCom: Topic Taxonomy Completion with Hierarchical Discovery of Novel Topic Clusters (WWW22)

    • Dongha Lee, Jiaming Shen, Seongku Kang, Susik Yoon, Jiawei Han, Hwanjo Yu | [Paper]

  • COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies (AAAI22)

    • Doyoung Kim, Hyangsuk Min, Youngeun Nam, Hwanjun Song, Susik Yoon, Minseok Kim, Jae-Gil Lee | [Paper][Code]

  • Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries (SIGMOD21)

  • Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping (KDD20)


Experiences


Services

  • Journal reviewer: VLDBJ, TKDE, DKE

  • Program committee: KDD22, AAAI22, KDD21 ODD (Outlier Detection and Description Workshop)