2026 CSUR Universal Time-Series Representation Learning: A Survey Patara Trirat, Yooju Shin, Junhyeok Kang, Youngeun Nam, Jihye Na, Minyoung Bae, Joeun Kim, Byunghyun Kim, and Jae-Gil Lee ACM Computing Surveys, 2026 PDF ACL Main QuDAR: Query-Wise Dual-Perspective Adaptive Retrieval Joeun Kim, Seunghyouk Yoon, Xuan-Bach Le, Youngeun Nam, Doyoung Kim, Hwanjun Song, and Jae-Gil Lee In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Main, 2026 2025 KDD Bi-Modal Learning for Networked Time Series Youngeun Nam*, Jihye Na*, Susik Yoon, Hwanjun Song, Jae-Gil Lee, and Byung Suk Lee In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025 PDF Video Poster ICWSM Mobility Networked Time-Series Forecasting Benchmark Datasets Jihye Na*, Youngeun Nam*, Susik Yoon, Hwanjun Song, Byung Suk Lee, and Jae-Gil Lee In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2025 PDF Poster KDD Mitigating Source Label Dependency in Time-Series Domain Adaptation under Label Shifts Jihye Na, Youngeun Nam, Junhyeok Kang, and Jae-Gil Lee In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025 PDF Video 2024 TheWebConf Breaking the time-frequency granularity discrepancy in time-series anomaly detection Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee, and Byung Suk Lee In Proceedings of the ACM on Web Conference (TheWebConf), 2024 PDF Video Poster KDD Semi-Supervised Learning for Time Series Collected at a Low Sampling Rate Minyoung Bae, Yooju Shin, Youngeun Nam, Young Seop Lee, and Jae-Gil Lee In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024 PDF Video 2023 ECML PKDD Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses Youngeun Nam, Patara Trirat, Taeyoon Kim, Youngseop Lee, and Jae-Gil Lee In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2023 PDF Poster Slides AAAI Demo AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series Patara Trirat*, Youngeun Nam*, Taeyoon Kim, and Jae-Gil Lee In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023 PDF Video Poster 2022 AAAI COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies Doyoung Kim, Hyangsuk Min, Youngeun Nam, Hwanjun Song, Susik Yoon, Minseok Kim, and Jae-Gil Lee In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022 PDF Video 2020 KDD Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea Minseok Kim, Junhyeok Kang, Doyoung Kim, Hwanjun Song, Hyangsuk Min, Youngeun Nam, Dongmin Park, and Jae-Gil Lee In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 PDF Video