Daokun Zhang
Scholar

Daokun Zhang

Google Scholar ID: ar_onRIAAAAJ
University of Nottingham Ningbo China
Graph LearningData MiningMachine Learning
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Citations & Impact
All-time
Citations
1,970
 
H-index
15
 
i10-index
20
 
Publications
20
 
Co-authors
4
list available
Contact
Emailmailto:?subject=Daokun%20Zhang&body=Check%20out%20this%20researcher%20at%20University%20of%20Nottingham%20Ningbo%20China%3A%20Daokun%20Zhang | http://research.nottingham.edu.cn/en/persons/daokun-zhang/?utm_source=email&utm_medium=email&utm_campaign=sharelTwitterOpen ↗LinkedInOpen ↗
Publications
8 items
CoMA: Complementary Masking and Hierarchical Dynamic Multi-Window Self-Attention in a Unified Pre-training Framework
2025
Cited
0
Layer-to-Layer Knowledge Mixing in Graph Neural Network for Chemical Property Prediction
2025
Cited
0
Towards the Next-generation Bayesian Network Classifiers
2025
Cited
0
WSI-Agents: A Collaborative Multi-Agent System for Multi-Modal Whole Slide Image Analysis
2025
Cited
0
CFFormer: Cross CNN-Transformer Channel Attention and Spatial Feature Fusion for Improved Segmentation of Low Quality Medical Images
2025
Cited
0
Label Distribution Learning using the Squared Neural Family on the Probability Simplex
arXiv.org · 2024
Cited
0
Combating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignment
arXiv.org · 2023
Cited
3
Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignment
Industrial Conference on Data Mining · 2022
Cited
7
Resume (English only)
Academic Achievements
  • - Published 27 papers (2016 to 2026)
  • - Scopus Citations: 14
  • - h-index: 14
Research Experience
  • - Assistant Professor, School of Computer Science, University of Nottingham Ningbo China, February 2024 - Present
  • - Research Fellow/Lecturer, Department of Data Science and AI, Monash University, April 2021 - January 2024
  • - Postdoctoral Research Associate, The University of Sydney, June 2019 - April 2021
Education
  • - Ph.D. in Data Science, University of Technology Sydney, August 31, 2015 to November 12, 2019
  • - Supervisor information not provided
Background
  • - Research Interests: Graph machine learning, specifically on graph representation learning, graph structure learning, node classification, and link prediction, etc.
  • - Application Areas: Knowledge graph completion and alignment, combinatorial optimization, computational material and drug discovery, particle system simulation, and geographic data forecasting, etc.
  • - Brief Introduction: Dr. Daokun Zhang has been an Assistant Professor at the School of Computer Science, University of Nottingham Ningbo China since February 2024. Prior to that, he worked as a Research Fellow/Lecturer at the Department of Data Science and AI, Monash University (April 2021 to January 2024), and as a Postdoctoral Research Associate at The University of Sydney (June 2019 to April 2021). He is dedicated to applying graph machine learning techniques to solve real-world problems across different disciplines.
Miscellany
  • - Teaching Courses: Linear and Discrete Optimization, Data Modelling and Analysis
  • - Interested in the following research topics: Weakly supervised learning with sparse/noisy labels, Uncertainty quantification for machine learning predictions, Next-generation Graph Neural Networks beyond feature smoothing
  • - Open to internal and external research collaborations
Co-authors
4 total
A/Prof. Jie Yin
A/Prof. Jie Yin
University of Sydney
Xingquan (Hill) Zhu
Xingquan (Hill) Zhu
IEEE Fellow, Dept. of Electrical Eng. and Comp. Science, Florida Atlantic University
Chengqi Zhang
Chengqi Zhang
Chair Professor of Artificial Intelligence
Shirui Pan
Shirui Pan
Professor, ARC Future Fellow, FQA, Director of TrustAGI Lab, Griffith University