About Me
I am currently a Research Fellow (Postdoc) at Nanyang Technological University (NTU), working under the supervision of Professor Jie Zhang. Previously, I was a Ph.D. candidate jointly trained at South China University of Technology (SCUT) and Institute for Infocomm Research (I2R), A*STAR. My doctoral study was supervised by Professor Qianli Ma (2021–2025) at SCUT and Dr. Min Wu (2024–2025), Head of the Model and Intelligence Chapter at the Institute for Advanced Intelligence and Computing (IAIC), A*STAR. My research primarily focuses on deep learning for time series analysis, with current interests in time series classification and time series foundation models. I am particularly interested in developing unified, scalable representation-learning frameworks that improve generalization and robustness in time-series classification.
Recent News
- 09/2026: One paper titled “From Retrieval to Recognition: Knowledge-Enhanced Post-training of Time Series Foundation Models for Classification” was accepted by NeurIPS 2026.
- 09/2026: Invited to serve as an Area Chair for ICLR 2027.
- 09/2026: One paper titled “EvoShape: Evolutionary Diffusion Shapelet Search for Semi-Supervised Time-Series Classification” was accepted by IEEE Transactions on Systems, Man, and Cybernetics: Systems.
- 01/2026: One paper titled “Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting” was accepted by ICLR 2026.
- 12/2025: One paper titled “CompleMatch: Boosting Time-Series Semi-Supervised Classification with Temporal-Frequency Complementarity” was accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence.
- 11/2025: One paper titled “A Unified Shape-Aware Foundation Model for Time Series Classification” was accepted by AAAI 2026.
- 05/2025: Three papers were accepted by ICML 2025.
- 10/2024: One paper titled “A survey on time-series pre-trained models” was accepted by IEEE Transactions on Knowledge and Data Engineering.
- 09/2024: One paper titled “Knowledge-Empowered Dynamic Graph Network for Irregularly Sampled Medical Time Series” was accepted by NeurIPS 2024.
- 05/2024: One paper titled “Incremental Sequence Labeling: A Tale of Two Shifts” was accepted by ACL 2024 (Findings).
- 12/2023: One paper titled “Diffusion Language-Shapelets for Semi-supervised Time-Series Classification” was accepted by AAAI 2024.
- 09/2023：One paper titled “Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels” was accepted by NeurIPS 2023.
- 04/2023：One paper titled “CTW: Confident Time-Warping for Time-Series Label-Noise Learning” was accepted by IJCAI 2023.
- 03/2023：One paper titled “Category-aware optimal transport for incomplete data classification” was accepted by Information Sciences 2023.
- 12/2022：One paper titled “Temporal-frequency co-training for time series semi-supervised learning” was accepted by AAAI 2023.
- 09/2019：One paper titled “Mechanical fault diagnosis and prediction in IoT based on multi-source sensing data fusion” was accepted by Simulation Modelling Practice and Theory 2020.