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Short Bio

My name is Zhong Li, and I am a final-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). I am currently working as a visiting PhD researcher in DAML group at Technical University of Munich, where I am fortunate to be supervised by Prof. Dr. Stephan Günnemann.

Research Interests:

I am interested in the field of Data Mining and Machine Learning. More specifically, I work on explainable and generalizable anomaly detection, with a focus on but not limited to complex data such as event sequence and graph-structured data.

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

ZhongLIFR's Projects

dejavu icon dejavu

Audio fingerprinting and recognition in Python

dig icon dig

A library for graph deep learning research

dufs icon dufs

Differentiable Unsupervised Feature Selection

jelsr icon jelsr

Unsupervised Feature Selection of Joint Embedding Sparse Regression Analysis

mvts-ano-eval icon mvts-ano-eval

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

py-soft-impute icon py-soft-impute

Python implementation of Mazumder and Hastie's softImpute for matrix completion

pygod icon pygod

A Python Library for Graph Outlier Detection (Anomaly Detection)

qcad icon qcad

Paper submitted to DAMI

refs icon refs

In this project I implemented "Reconstruction-based Unsupervised Feature Selection" method for feature selection

shazam icon shazam

Music Identification Program based on Shazam's methods

shazoinks icon shazoinks

Shazam clone written in Python from Harvard CS51 final project

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