Xin Zheng

Xin Zheng

Assistant Professor @ RMIT University

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I am an Assistant Professor in the Data Science and Artificial Intelligence (DSAI) Discipline, School of Computing Technologies, RMIT University, Australia. Previously, I was an Assistant Professor in the School of ICT at Griffith University and a member of the TrustAGI Lab, led by Prof. Shirui Pan. I received my Ph.D. from Monash University, where I worked closely with Prof. Shirui Pan and Prof. Chunyang Chen.
My research focuses on: (1) Data-centric AI; (2) Automated Graph Machine Learning; (3) AI for Science. My work has been published in leading journals and conferences, including IJCV, ICML, NeurIPS, ICLR, AAAI, and WWW.

Prospective Ph.D. Students. I am looking for highly self-motivated Ph.D. students interested in Data-centric AI, LLM agent, AI4Healthcare, and AI4SE. Applicants with strong programming backgrounds are encouraged to apply. Also welcome CSC-funded Ph.D. applicants. Please send your CV and academic transcript to zhengxin.phd@gmail.com.

Xin Zheng
Dr. Xin Zheng
Assistant Professor
RMIT University, Melbourne, Australia

News

Service

  • Organizing Roles
    • Workshop Chair, 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2025.
  • Program Committee & Reviewer
    • Conferences: ICML, NeurIPS, ICLR, ICDM, KDD, IJCAI, CIKM, WWW, PAKDD, ACM MM, etc.
    • Journals: IEEE TPAMI, IEEE TNNLS, IEEE TKDE, Pattern Recognition, Neural Networks, etc.
  • Invited Talks / Speaking
    • ARC Training Center Information Resilience PhD School — Automated Graph MLOps, University of Queensland, Brisbane, Australia, 2024.
    • Australia Database Conference (ADC), University of Melbourne, Melbourne, Australia, 2023.

Selected Research

Data-centric AI; AI4Science; Security

Data-Centric AI

Data-level: Scalability & Diversity;

ICML 2025 | Zheng, Xin, et al. "Test-Time Graph Neural Dataset Search With Generative Projection." Paper Code Slides
NeurIPS 2023 | Zheng, Xin, et al. "Structure-free graph condensation: From large-scale graphs to condensed graph-free data." Paper Code Slides
arXiv 2023 | Zheng, Xin, et al. "Towards data-centric graph machine learning: Review and outlook." Paper Code Slides
arXiv 2022 | Zheng, Xin, et al. "Graph neural networks for graphs with heterophily: A survey." Paper Code Slides

Model-level: Automation, Data-driven & Task-driven;

WWW 2023 | Zheng, Xin, et al. "Auto-heg: Automated graph neural network on heterophilic graphs." Paper Code Slides
ICDM 2022 | Zheng, Xin, et al. "Multi-relational graph neural architecture search with fine-grained message passing." Paper Code Slides

Application-level: Test-time Adaptation & Model Evaluation.

IJCAI 2025 | Liu, Yating, ..., Zheng, Xin, et al. "Test-time adaptation on recommender system with data-centric graph transformation." Paper Code Slides
ICDM 2025 | Zheng, Xin, et al. "Test-Time Graph Rebirth: Serving GNN Generalization Under Distribution Shifts." Paper Code Slides
ICDM 2025 | Li, Bo, ..., Zheng, Xin, et al. "Test-time GNN Model Evaluation on Dynamic Graphs." Paper Code Slides
ICLR 2024 | Zheng, Xin, et al. "Online GNN Evaluation Under Test-time Graph Distribution Shifts." Paper Code Slides
NeurIPS 2023 | Zheng, Xin, et al. "GNNEvaluator: Evaluating GNN performance on unseen graphs without labels." Paper Code Slides

AI for Science

CIKM 2025 | Li, Bo, ..., Zheng, Xin, et al. "Oasis: Harnessing diffusion adversarial network for ocean salinity imputation using sparse drifter trajectories." Paper Code Slides
PAKDD 2025 | Zhou, Ruipeng, ..., Zheng, Xin, et al. "Efficient and Diverse De Novo Protein Backbone Design with SE (3)-Equivariant Diffusion." Paper Code Slides
arXiv 2025 | Wang, Zeyu, ..., Zheng, Xin, et al. "Few-shot molecular property prediction: A survey." Paper Code Slides

Security & Robustness

NeurIPS 2025 | Wang, Zeyu, ..., Zheng, Xin, et al. "Data-Free Model Extraction for Black-box Recommender Systems via Graph Convolutions." Paper Code Slides

Team Members

Ph.D. / Master / Visiting Students

I am fortunate to collaborate with a group of outstanding and passionate students. Their dedication, creativity, and willingness to explore challenging problems play a central role in the growth and direction of our research.

Bo Li
Ph.D.
Griffith University (Australia)
Dynamic Graph Learning
Research Outputs: CIKM 2025; ICDM 2025 (×2).
LinkedIn
Zeyu Wang
Visiting Ph.D.
Griffith University (Australia) | Zhejiang University of Technology (China)
Molecular Property LearningRecSys Security
Research Outputs: NeurIPS 2025; arXiv 2025 (Survey).
GitHub Google Scholar
Hongjiang Chen
Upcoming Visiting Ph.D.
Griffith University (Australia) | Hangzhou Dianzi University (China)
Dynamic Graph Explainability Multi-LLM Agents
Research Outputs: IJCAI 2025 (×2); PR 2026; In Progress.
Google Scholar
Ming Yang
Upcoming Visiting Ph.D.
Monash University (Australia) | Dalian University of Technology (China)
AI4Bio Protein Design
Research Outputs: PAKDD 2025; In Progress.
Huanchang Ma
Ph.D.
Northeast Normal University (China)
Test-time Model Evaluation AI4Healthcare
Research Outputs: In Progress.
Yating Liu
M.Sc.
Dalian University of Technology (China)
Test-time Adaptation Recommender Systems
Research Outputs: IJCAI 2025.
Jian Zhang
M.Sc. | Research Assistant
University of Sydney (Australia)
AI4Healthcare Automated Machine Learning
Research Outputs: In Progress.
Jiayi Wang
M.Sc.
Dalian University of Technology (China)
Multi-domain Adaptation
Research Outputs: ADMA 2025.
Fuxin Yu
M.Sc.
Dalian University of Technology (China)
Graph Condensation AI for Software Engineering
Research Outputs: In Progress.
Jiayi Chen
M.Sc.
Dalian University of Technology (China)
Multi-modal RecSys Test-time Adaptation
Research Outputs: In Progress.
Boda Duan
M.Sc.
Dalian University of Technology (China)
AI4Healthcare Diffusion Model
Research Outputs: In Progress.
Shuo Li
M.Sc.
Guangxi University (China)
AI4Healthcare Graph RAG
Research Outputs: In Progress.
Ting Wei
M.Sc.
Guangxi University (China)
Graph Anomoly Detection
Research Outputs: In Progress.