About me

I am currently an Associate Professor at the School of Software Engineering, Sun Yat-Sen University (SYSU). Previously, I worked as a postdoctoral researcher with Professor See-Kiong Ng at the Institute of Data Science (IDS), National University of Singapore (NUS). I obtained my Ph.D. in 2017 from Nanyang Technological University (NTU), under the supervision of Professor Hu Guoqiang and Professor Costas J. Spanos from the University of California, Berkeley (UCB). Prior to that, I received my Bachelor's degree from the University of Electronic Science and Technology of China (UESTC).

My current research interests include Data-Centric AI, Time Series Data Analysis, Time Series Foundation Models, and related applications.

I am also interested in anomaly detection and fault diagnosis in the industrial field, such as CPS and IIoT.

I am seeking self-motivated undergraduate interns and graduate students with strong mathematical backgrounds and coding skills. 

My research team is recruiting post-doc researchers!

Feel free to drop me an email with your CV if interested. 

What's New

May 2026: One paper is accepted to ICML 2026!

April 2026: We will give a tutorial named "Trustworthy Foundation Models via A Data-Centric Lens" at DASFAA 2026!

March 2026: Our Time Series Foundation Model (WaveMoE) will be presented at TSALM@ICLR 2026!

Jan 2026: One paper is accepted to ICLR 2026, and one paper is accepted to DASFAA 2026!

Dec 2025: Our paper got the best paper award at PHM AP 2025!

July 2025: I am serving as a track chair of PHM AP 2025.

July 2025: One paper is accepted to CIKM 2025.

June 2025: One paper is accepted to USENIX Sec.

May 2025: I was invited to give a talk at Blocksys 2025.

May 2025: I was invited to give a talk at ICSS 2025.

March 2025: Our paper ``LicenseGPT: A Fine-tuned Foundation Model for Publicly Available Dataset License Compliance '' was accepted by FSE 2025.

November 2024: Our paper ``BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction'' got the best student paper award at EAI CollaborateCom 2024!

Selected Publications

#-indicates student collaborators

Jiahui Zhou#, Dan Li, Boxin Li, Xiao Zhang, Erli Meng, Lin Li#, Zhuomin Chen#, Jian Lou, See-Kiong Ng, “Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoning", ICML, 2026

Jiawen Zhang, Yangfan Hu, Kejia Chen, Lipeng He, Jiachen Ma, Jian Lou, Dan Li, Jian Liu, Xiaohu Yang, Ruoxi Jia, “Understanding and Preserving Safety in Fine-Tuned LLMs", ACM CCS, 2026.

Shunyu Wu#, Jiawei Huang#, Weibin Feng#, Boxin Li, Xiao Zhang, Erli Meng, Dan Li, Jian Lou, See-Kiong Ng, “WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting", TSALM@ICLR, 2026.

S. Wu#, D.Li, Wenjie Feng, H. Ye#, J. Lou, S. K. Ng, “Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgment", ICLR, 2026.

S. Wu#, T. Li#, Y. Leng#, J. Suo#, J. Lou, D. Li, S. K. Ng, “Lightweight Time Series Data Valuation on Time Series Foundation Models via In-Context Finetuning", DASFAA, 2026.

S. Shan#, Y. Huo, Y. Su, Z. Wang, D. Li, Z. Zheng, ConfLogger: Enhance Systems' Configuration Diagnosability through Configuration Logging, ICSE, 2026.

J. Zhang, K. Chen, L. He, J. Lou, D. Li, Z. Feng, M. Song, J. Liu, K. Ren, X. Yang, Activation approximations can incur safety vulnerabilities even in aligned llms: Comprehensive analysis and defense, USENIX Sec, 2026.

H. Qaid#, B. Zhang, D. Li, S.K. Ng, W. Li, FD-LLM: Large Language Model for Fault Diagnosis of Machines, Engineering Applications of Artificial Intelligence, 2025

R. Hu#, D. Li, J. Lou, R. Jin, B. Lin, W. Li, S.K. Ng, Z. Zheng, Restoring Missing Gaps and Intervals via Global Consistency and Local Coherence, Expert Systems with Applications, 2025.

Z. Chen#, D. Li, J. Zhou#, S. Wu#, H. Ye#, J. Lou, S.K. Ng, Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting， CIKM, 2025.

J. Tan#, G. K. Rajbahadur, Z. Li, X. Song, J. Lin, D. Li, Z. Zheng, A. E. Hassan, LicenseGPT: A Fine-tuned Foundation Model for Publicly Available Dataset License Compliance, FSE, 2025.  

H. Yang#, J. Fang, J. Wu, D. Li, Y. Wang, Z. Zheng, Soft label enhanced graph neural network under heterophily,  Knowledge-Based Systems,  2025.

S. Shan#, Y. Huo, Y. Su, Y. Li, D. Li, Z Zheng, Face It Yourselves: An LLM-Based Two-Stage Strategy to Localize Configuration Errors via Logs, ISSTA, 2024.

Z. Zhang#, D. Li, S. Wu#, J. Cai#, B. Zhang, S. K. Ng, Z. Zheng, BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction, CollaborateCom, 2024. 

G. Tu#, D. Li,  S. Ng, Z. Zheng, GLA-DA: Global-Local Alignment Domain Adaptation for Multivariate Time Series, DASFAA, 2024.

R. Hu#, D. Li,  S. Ng, Z. Zheng, CB-GAN: Generate Sensitive Data with a Convolutional Bidirectional Generative Adversarial Networks, DASFAA, 2023. 

P. Qi#, D. Li, and S. Ng. MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks, ICDE, 2022.