Scholar
Zhen Liu
Google Scholar ID: M5qB8dsAAAAJ
Ph.D Student, South China University of Technology
Citations & Impact
Citations
485
H-index
9
i10-index
9
Publications
16
Co-authors
9
list available
Contact
Publications
Resume (English only)
Academic Achievements
- May 2025: Three papers were accepted by ICML 2025.
- October 2024: One paper titled “A survey on time-series pre-trained models” was accepted by IEEE Transactions on Knowledge and Data Engineering 2024.
- September 2024: One paper titled “Knowledge-Empowered Dynamic Graph Network for Irregularly Sampled Medical Time Series” was accepted by NeurIPS 2024.
- May 2024: One paper titled “Incremental Sequence Labeling: A Tale of Two Shifts” was accepted by ACL 2024 (Findings).
- December 2023: One paper titled “Diffusion Language-Shapelets for Semi-supervised Time-Series Classification” was accepted by AAAI 2024.
- September 2023: One paper titled “Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels” was accepted by NeurIPS 2023.
- April 2023: One paper titled “CTW: Confident Time-Warping for Time-Series Label-Noise Learning” was accepted by IJCAI 2023.
- March 2023: One paper titled “Category-aware optimal transport for incomplete data classification” was accepted by Information Sciences 2023.
- December 2022: One paper titled “Temporal-frequency co-training for time series semi-supervised learning” was accepted by AAAI 2023.
- September 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.
Research Experience
- Currently in the fourth (final) year of pursuing a Ph.D.
Education
- Ph.D. student at South China University of Technology and Institute for Infocomm Research, A*STAR, under the mentorship of Professor Qianli Ma and Principal Scientist Min Wu.
Background
- Research Interests: Deep learning, specifically focusing on time series classification, time series pre-training, semi-supervised learning, label noise learning, and incomplete data analysis. Professional Field: Computer Science.
Miscellany
- Homepage: https://skylerhallinan.com/, powered by Jekyll & AcademicPages, a fork of Minimal Mistakes.
