The ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) is one of the oldest and most prestigious international conferences in the fields of data science, data mining, and knowledge discovery. Sponsored by the SIGKDD professional group of the Association for Computing Machinery (ACM), KDD is recognized as a Class A conference by the China Computer Federation (CCF). The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining will take place from August 9 to 13, 2026, at the Jeju International Convention Center in Jeju, South Korea.
The KDD 2026 acceptance results have recently been announced. Faculty and students from the Industrial Informatics and Intelligence Institute (Triple-I Institute) at The Hong Kong University of Science and Technology (Guangzhou) have delivered an outstanding performance, with a total of 11 high-quality papers accepted by the conference, fully demonstrating the Institute’s exceptional research strength in the field of data science.
Paper one
MedTVL: Harnessing Vision and Language for Medical Time Series Classification
Author: Jiexia Ye, Jia Li, Fugee Tsung
Paper two
Hierarchical Reinforcement Learning for Cooperative Air-Ground Delivery in Urban System
Author: Songxin Lei, Chunming Ma, Haomin Wen, Yexin Li, Lizhenghe Chen, Qianyu Yang, Fugee Tsung, Lei Chen, Sijie Ruan, Yuxuan Liang
Paper three
Fourier Geometric Wind Power Forecasting with Numerical Weather Prediction
Author: Shiyuan Piao, FAN Zehui, Yang Liu, Hong Cheng, Juepeng Zheng, Jie Zhou, Fugee Tsung
Paper four
TA-TFN: Task-Adaptive Frequency Decoupling for Generalizable Battery State Estimation across Chemistries
Author: Jing Wang, Shiyuan Piao, Fugee Tsung
Paper five
IMGNN: an Efficient, Effective and Generalizable Algorithm for Influence Maximization in Social Networks
Author: Haotian Zhang, Kai Han, Zhizhuo Yin, Shuang Cui, Jing Tang, Pan Hui
Paper six
Signed Proximity Matters in Graph-based Recommendation
Author: Yifan Song, Renchi Yang, Jing Tang
Paper seven
Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling
Author: Xixuan Hao, Yutian Jiang, Jiabo Liu, Yihang Yang, Guangyin Jin, Song Gao, Yuxuan Liang
Paper eight
TS-Memory: Plug-and-Play Memory for Time Series Foundation Models
Author: Sisuo Lyu, Siru Zhong, Tiegang Chen, Weilin Ruan, Qingxiang Liu, Taiqiang Lv, Qingsong Wen, Raymond Chi-Wing Wong, Yuxuan Liang
Paper nine
UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
Author: Wei Chen, Yuqian Wu , Junle Chen, Xiaofang Zhou, Yuxuan Liang
Paper ten
How to Train Your Mamba for Time Series Forecasting
Author: Jiaxi Hu, Disen Lan, Ziyu Zhou, Gefeng Luo, Qingsong Wen, Yuxuan Liang
Paper eleven
Label Annotation for Tabular Anomaly Detection with Large Language Models
Author: Haihong Zhao, Aochuan Chen, Miao Peng, Xiaolong Fan, Daowei Lin, Xuan Zong, Jun Zhou , Jia Li