Zhangkai Wu

PhD candidate

FEIT

University of Technology Sydney

Current Research Topics

Deep Probabilistic Generative Models
- VAE, Diffusion, BFN
Representation Learning
Image Editing
Time Series Anomaly Detection

About Me

I am Zhangkai Wu. I am currently a PhD candidate in FEIT at the University of Technology Sydney. Fortunately, I am supervised by Distinguished Chair Professor Longbing Cao. Previously, I received my M.Eng. in Reasoning & Learning group supervised by professor Yang Gao Nanjing University in 2018 and B.Eng. degree in School of Information Engineering at GuangXi University in 2014.

News

[2024-07] 🔥 Actively seeking Postdoctoral positions in the field of Generative AI.
[2024-11] Two papers are accepted by the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025.

Preprints

C2VAE: Gaussian Copula-based VAE Differing Disentangled from Coupled Representations with Contrastive Posterior

Zhangkai Wu, Longbing Cao

arXiv preprint arXiv:2309.13303 [Paper]

Publications

ProgDiffusion: Progressively Self-encoding Diffusion Models

Zhangkai Wu, Xuhui Fan, Longbing Cao

KDD 2025 (Acceptance rate: 19%) [Paper] [Code]

ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks

Zhangkai Wu, Xuhui Fan, Jin Li, Zhilin Zhao, Hui Chen, Longbing Cao

KDD 2025 (Acceptance rate: 19%) [Paper] [Code]

Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection

Zhangkai Wu, Longbing Cao, Qi Zhang, Junxian Zhou, Hui Chen

Information Fusion (Impact Factor 14.7 in 2025) [Paper] [Code]

eVAE: Evolutionary Variational Autoencoder

Zhangkai Wu, Longbing Cao, Lei Qi

IEEE Transactions on Neural Networks and Learning Systems(TNNLS, Impact Factor 10.4 in 2025) [Paper]

Local Descriptor-based Multi-prototype Network for Few-shot Learning

Hongwei Huang^*, Zhangkai Wu^*, Wenbin Li, Jing Huo, Yang Gao

Pattern Recognition (PR) 2021 [Paper]

Differentiable Meta-learning Model for Few-shot Semantic Segmentation

Pinzhuo Tian, Zhangkai Wu, Lei Qi, Lei Wang, Yinghuan Shi, Yang Gao

33th AAAI Conference on Artificial Intelligence (AAAI19) [Paper]

Services

Program Committee Member: IJCAI24-25, NeurIPS24, DSAA24, ICLR25, ECMLPKDD25, AISTATS25,ICML25.

Journal Reviewer: TIP, TOMM, TCSS, CSUR, Information Fusion, Machine Learning (MLJ), IS (IEEE Information System).

Teaching and Tutorials

Seasonal Tutor for Advanced Machine Learning (2024S2, COMP8221) at School of Computer Science, Macquarie University.
Guest Lecture in Data Science course over 1,000 students (2024S2, COMP220/6200) at School of Computer Science, Macquarie University .
Tutorial for Deep Variational Learning in IJCAI2024 at Jeju.
Guest Lecture in Emerging Topics in AI (2022S1) at FEIT, University of Technology of Sydney.
Seasonal Tutor for Advanced Machine Learning (2020S2) at School of Software engineering, Nanjing University .

Correspondence

Email: ZHANGKAI.WU@student.uts.edu.au

Address: Zhangkai Wu, Data Science Institute, Level 12, Building 2, UNIVERSITY OF TECHNOLOGY SYDNEY, 61 BROADWAY, Sydney, Australia.