Explanatory Data Analysis group
Zhong is currently a PhD student in Machine Learning at LIACS (Leiden Institute of Advanced Computer Science) under the supervision of dr. Matthijs van Leeuwen. Zhong's research interests mainly focus on machine learning, especially in anomaly detection. More specifically, his PhD program centers on the topic of "Feature and data subset selection for contextual anomaly detection using hybrid models", which is part of the DIGITAL TWIN programme funded by NWO.
Before joining Leiden University, Zhong obtained a bachelor's degree in Statistics from Tongji University in Shanghai. Later, he received a Master's degree in Mathematics from Tongji University in Shanghai and a double degree(Diplôme d'Ingénieur) in Data Science from ENSAI in Rennes, France.
In addition to theoretical innovation, Zhong also hopes to successfully apply his research to industries, such as the preventive maintenance of high-end machines, trading compliance in banks, and healthcare in hospitals, etc.
Zhong has always followed the principle of "Tao follows nature". In addition to his interest in mathematics and computer science, he is also passionate about biology, physics, and philosophy. This is because he always believes that things in the universe are interconnected by some kind of universe law, and he likes to get inspiration from various natural and social phenomena.
Selected recent publications
Feature Selection for Fault Detection and Prediction based on Event Log Analysis. ACM SIGKDD Explorations vol.24(2), ACM, 2022.
Feature Selection for Fault Detection and Prediction based on Log Analysis. In: Proceedings of the international workshop on AI for Manufacturing Workshop at ECMLPKDD 2022, 2022.