Zhichen Lai 赖志宸

About Me

I am a Ph.D. Candidate of the Department of Computer Science at Aalborg University (AAU), Denmark, supervised by Prof. Christian S. Jensen, Assoc. Prof. Dalin Zhang, and Prof. Huan Li (Zhejiang University, China). I am also a member of the Data Engineering, Science and Systems (DESS) group. Additionally, I collaborate closely with Prof. Hua Lu, Assoc. Prof. Xiufeng Liu and Prof.Xu Cheng. From June to August 2024, I will be a Junior Visiting Research Fellow at the School of Computer Science and Engineering, University of New South Wales (UNSW), Australia.

I obtained my master’s degree in Computer Science from the Data Intelligence and Computing Art Lab at Sichuan University (SCU), China, under the supervision of Prof. Jiancheng Lv in 2021. Prior to that, I earned my bachelor’s degree in Computer Science from University of Electronic Science and Technology of China (UESTC) in 2018.

My primary research areas are Data Management and Analytics. Specifically, my current research interests are as follows:

• Lightweight AI for Sensory Data Analytics
• Spatio-temporal Data Applications
• Smart Meter Data Analytics

My hobbies are travelling, singing, and making crafts.

Selected Publications

1. Lai, Z., Zhang, D., Li, H., Zhang, D., Lu, H., & Jensen, C. S.. (2024). ReCTSi: Resource-efficient Correlated Time Series Imputation via Decoupled Pattern Learning and Completeness-aware Attentions. KDD 2024 (CORE-A*, CCF-A).

2. Lai, Z., Zhang, D., Li, H., Jensen, C. S., Lu, H., & Zhao, Y. (2024). Lightweight Correlated Time Series Forecasting Enhanced with Model Distillation. IEEE Transactions on Knowledge and Data Engineering ( Minor Revision, JCR Q1, CCF-A).

3. Lai, Z., Li, H., Zhang, D., Zhao, Y., Qian, W., Jensen, C. S., & Zhao, Y. (2024). E2USD: Efficient-yet-effective Unsupervised State Detection for Multivariate Time Series. WWW 2024 (CORE-A*, CCF-A).

4. Lai, Z., Zhang, D., Li, H., Jensen, C. S., Lu, H., & Zhao, Y. (2023). LightCTS: A Lightweight Framework for Correlated Time Series Forecasting. SIGMOD 2023 (CORE-A*, CCF-A).

5. Lai, Z., Cheng, X., Liu, X. (2022). Multiscale Wavelet-driven Graph Convolutional Network for Blade Icing Detection of Wind Turbines. IEEE Sensors Journal (JCR Q1).

6. Lai, Z., Tang, C., & Lv, J. (2020). Arbitrary Chinese Font Generation from a Single Reference. IJCNN 2020 (CORE-A).

7. Lai, Z., Tang, C., & Lv, J. (2019). Multi-view Image Generation by Cycle CVAE-GAN Networks. ICONIP 2019 (CORE-A).

8. Liu, X., Lai, Z.*, Wang, X., & Nielsen, P. S. (2020). A Contextual Anomaly Detection Framework for Energy Smart Meter Data Stream. ICONIP 2020 (CORE-A).

9. Li, M., Lv, J., Tang, C., Wang, J., Lai, Z., & Huang, Y. (2020). Combination of Certainty and Uncertainty: Using FusionGAN to Create Abstract Paintings. Neural Networks (JCR Q1, CCF-B).

10. Chen, L., Lai, Z., Liu, D., Lv, J., & Sang, Y. (2020). Exploration on the Generation of Chinese Palindrome Poetry. ICONIP 2020 (CORE-A).

11. Wan, P. K., Lai, Z., Liu, X., Nowostawski, M., & Holtskog, H. (2022). Automated Infection Risks Assessments for Decision-making Using a Blockchain-based Alert System: A Case Study in a Representative Building. Environmental Research (JCR Q1).

Talks

• The Web Conference, May 2024.
• The Academy of Digital China, Fuzhou University, Jan 2024.
• SIGMOD Conference, June 2023.
• College of Computer Science and Technology, Zhejiang University, Mar 2023.
• School of Cyber Engineering, Xidian University, Feb 2023.

Services

Reviewer

• KDD, IEEE TNNLS, AAAI, CIKM, Machine Learning, Expert Systems with Applications, IEEE BigData, ACM SIGSPATIAL, Royal Society Open Science, IJCNN, ICONIP etc.

Program Committee Member

• KDD 2024, AAAI 2024, DSAA 2022, HDIS 2022.

Awards

• Sichuan Provincial Outstanding Graduate,
• SCU Outstanding Student,
• SCU Outstanding Graduate,
• Huawei-SCU Scholarship,
• UESTC Excellent Bachelor Degree Dissertation, etc.

Last Updated 2024-05-17