Ph.D. Student, Institute of Computing Technology, Chinese Academy of Sciences
Researcher in Time Series, Spatio-Temporal Learning, and AI for Science
I work on data-centric machine learning for scientific discovery, with a particular focus on time series forecasting, spatio-temporal modeling, and robust evaluation of AI systems. I am also engaged in foundational research on frontier applications of large models at Baidu.
Time series forecasting, spatio-temporal learning, AI for Science, data-centric AI, and robust model evaluation.
- ARIES arxiv — Time-series modeling and evaluation
- APT AAAI26 — Predictive modeling under distribution drift
- BLAST KDD25 — Balanced corpus construction for time series
- STA-GANN CIKM25 — Spatio-temporal kriging
- DFDGCN ICASSP24— Dynamic graph learning for spatio-temporal prediction
- TULMGAT PR25 — Trajectory user linking
- Benchmarking for time series foundation models;
- Pattern-aware corpus construction and evaluation;
- Distribution shift and model robustness;
- Scientific AI systems for real-world applications.
Open to research collaborations in related areas.
- Google Scholar: Yujie Li
- Email: liyujie231@mails.ucas.ac.cn
