Short Bio

[I am moving to a new homepage, and this one will no longer be maintained since Nov 2024.]

My name is Zhong Li, and I am a fourth-year Ph.D. candidate in Computer Science at Leiden University, affiliated with the EDA Lab. I am fortunate  to be supervised  by Dr. Matthijs van Leeuwen (daily supervisor, promotor) and Prof. Dr. Thomas Bäck (promotor). Besides, I worked as a visiting PhD researcher in the DAML group at Technical University of Munich in 2024, supervised by Prof. Dr. Stephan Günnemann. 

Research Interests: 

I am interested in the field of Data Mining and Machine Learning. During my PhD, I work on trustworthy anomaly detection, with a focus on but not limited to complex data such as event sequence and graph-structured data for smart manufacturing.

More concretely, I aim to improve the accuracy (namely make anomaly detection models more accurate, especially with high-dimensional, unstructured, multimodal data), explainability (namely make anomaly detection models more understandable for humans) and generalizability (namely make anomaly detection models work reliably under changing conditions such as data distribution shifts, uncharted hyperarameter configurations, and the presence of adversarial perturbations) of anomaly detection methods.

Research Keywords: 

• Methodologies-Oriented: Unsupervised Machine Learning; Anomaly Detection; Transfer Learning; XAI; Graph Neural Networks

• Applications-Oriented: Log Analysis; Predictive Maintenance; Digital Twin; AI for Manufacturing

Experience

• 2020.11 - 2025.02 (Expected):  PhD Candidate in Computer Science, Leiden University, Leiden, the Netherlands

• 2024.03 - 2024.06:  Visiting PhD Researcher in Computer Science, TU Munich, Munich, Germany 

• 2017.09 - 2019.10:  Diplôme d'Ingénieur in Data Science, ENSAI, Rennes, France (EIFFEL excellence scholarship recipient)

• 2016.09 - 2020.03:  Master's degree in Mathematics, Tongji University, Shanghai, China

• 2012.09 - 2016.06:  Bachelor’s degree in Statistics, Tongji University, Shanghai, China (Graduating With Honors, top 5%)

Recent News

• 💥News: Our paper titled Cross-domain Graph Level Anomaly Detection  is accepted by TKDE for publication! (September 2024)

• 💥News: Our paper titled Graph Neural Networks based Log Anomaly Detection and Explanation  is accepted by ICSE'24 poster track! (January 2024)

• 💥News: Our paper titled A survey on explainable anomaly detection  is accepted by TKDD for publication! (July 2023)

• 💥News: Our paper titled Explainable Contextual Anomaly Detection using Quantile Regression Forests  is accepted by DAMI for publication! (June 2023)

• [Open Position] (Position-Cancelled) I am looking for a Master student to do an internship&master thesis, which will be in collaboration with Canon. The thesis proposal is "Knowledge-based & Data-driven Inkjet Jet Failure Detection and Classification".  (October 2023)

• [Open Position] (Position-Filled): I am looking for a Master student to do an internship&master thesis, which will be in collaboration with VDL & ASML. The thesis proposal is "Predictive Maintenance of Lithography System Using Log Anomaly Detection".  (June 2023)