Tsinghua University / Industrial Engineering
Ph.D. student in AI & machine learning
I study causal structure and reliable machine learning for temporal and multimodal data.
I am a Ph.D. student at Tsinghua University (2023–present), advised by Prof. Chen Zhang. I received my B.Eng. in Industrial Engineering from Tsinghua in 2023. My work spans causal discovery, foundation models for time-series anomaly detection, and dynamic systems.
139 citations 7 h-index 6 i10-indexUpdated 2026-09-17
SCALE, our work on online latent-domain anomaly detection, was accepted to KDD 2026.
Our work on foundation models for zero-shot time-series anomaly detection was accepted to ICML 2026. arXiv
New preprint: VETime, vision-enhanced zero-shot time-series anomaly detection. arXiv
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Time Series Anomaly
Foundation models for zero-shot time series anomaly detection using synthetic data and context discrepancy.
International Conference on Machine Learning (ICML), 2026
Causal Discovery
Dynamic latent variable modeling for nonlinear causal discovery with applications.
IEEE Transactions on Automation Science and Engineering, 2025
Causal Graphs
Multi-task DAG learning with application to traffic congestion analysis.
KDD 2023
Time Series Anomaly
Explainable time series anomaly detection leveraging large language models.
arXiv preprint arXiv:2509.24378
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* Equal contribution.
Industrial Engineering · Advised by Prof. Chen Zhang
Causal graph learning for urban traffic
Industrial Engineering
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For research discussions and collaboration.