2026 James Bailey: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	56	3981	3869	113	112	349	17983

Overview

James Bailey is affiliated with the University of Melbourne in Australia. Their research primarily centers on computer science, with a concentration in artificial intelligence, computer vision and pattern recognition, signal processing, human-computer interaction, and molecular biology.

The main topics of their work include:

Adversarial Robustness in Machine Learning
Anomaly Detection Techniques and Applications
Machine Learning and Data Classification
Advanced Neural Network Applications
Domain Adaptation and Few-Shot Learning
Human Pose and Action Recognition
Integrated Circuits and Semiconductor Failure Analysis

James Bailey has contributed extensively to various academic venues. Frequent publication outlets include:

arXiv (Cornell University)
Proceedings of the AAAI Conference on Artificial Intelligence
APL Machine Learning
CHI Conference on Human Factors in Computing Systems
Proceedings of the Annual Hawaii International Conference on System Sciences

Coauthors frequently collaborating with Bailey consist of:

Xingjun Ma
Sarah Erfani
Hanxun Huang
Yisen Wang
Qiuhong Ke

Recent publications highlight Bailey's work on adversarial robustness and machine learning techniques. Selected papers include:

Understanding adversarial attacks on deep learning based medical image analysis systems, 2020, Pattern Recognition
On the Convergence and Robustness of Adversarial Training, 2021, arXiv (Cornell University)
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets, 2020, arXiv (Cornell University)
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression, 2021, arXiv (Cornell University)
Normalized Loss Functions for Deep Learning with Noisy Labels, 2020, arXiv (Cornell University)

Best Publications

Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance

Nguyen Xuan Vinh;Julien Epps;James Bailey

2773
Citations
Information theoretic measures for clusterings comparison: is a correction for chance necessary?

Nguyen Xuan Vinh;Julien Epps;James Bailey

1059
Citations
Symmetric Cross Entropy for Robust Learning With Noisy Labels

Yisen Wang;Xingjun Ma;Zaiyi Chen;Yuan Luo

979
Citations
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

Xingjun Ma;Bo Li;Yisen Wang;Sarah M. Erfani

553
Citations
Understanding adversarial attacks on deep learning based medical image analysis systems

Xingjun Ma;Yuhao Niu;Lin Gu;Yisen Wang

488
Citations
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks

Yunfei Liu;Xingjun Ma;James Bailey;Feng Lu

485
Citations
Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

James Bailey;Alistair Moffat;Charu C. Aggarwal;Maarten de Rijke

362
Citations
Iterative Learning with Open-set Noisy Labels

Yisen Wang;Weiyang Liu;Xingjun Ma;James Bailey

342
Citations
Improving Adversarial Robustness Requires Revisiting Misclassified Examples

Yisen Wang;Difan Zou;Jinfeng Yi;James Bailey

311
Citations
Dimensionality-Driven Learning with Noisy Labels

Xingjun Ma;Yisen Wang;Michael E. Houle;Shuo Zhou

293
Citations
Discovery of minimal unsatisfiable subsets of constraints using hitting set dualization

James Bailey;Peter J. Stuckey

253
Citations
Identifying at-risk students in massive open online courses

Jiazhen He;James Bailey;Benjamin I. P. Rubinstein;Rui Zhang

250
Citations
Normalized Loss Functions for Deep Learning with Noisy Labels

Xingjun Ma;Hanxun Huang;Yisen Wang;Simone Romano

237
Citations
Computer-Aided Diagnosis of Melanoma Using Border- and Wavelet-Based Texture Analysis

R. Garnavi;M. Aldeen;J. Bailey

234
Citations
Clean-Label Backdoor Attacks on Video Recognition Models

Shihao Zhao;Xingjun Ma;Xiang Zheng;James Bailey

226
Citations
Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles

Ranjie Duan;Xingjun Ma;Yisen Wang;James Bailey

221
Citations
Mining minimal distinguishing subsequence patterns with gap constraints

Xiaonan Ji;J. Bailey;Guozhu Dong

218
Citations
Adjusting for chance clustering comparison measures

Simone Romano;Nguyen Xuan Vinh;James Bailey;Karin Verspoor

218
Citations
is-rSNP

Geoff Macintyre;James Bailey;Izhak Haviv;Izhak Haviv;Izhak Haviv;Adam Kowalczyk

215
Citations
An Event-Condition-Action Language for XML.

James Bailey;George Papamarkos;Alexandra Poulovassilis;Peter T. Wood

214
Citations
An event-condition-action language for XML

James Bailey;Alexandra Poulovassilis;Peter T. Wood

212
Citations
On the convergence and robustness of adversarial training

Yisen Wang;Xingjun Ma;James Bailey;Jinfeng Yi

192
Citations
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets

Dongxian Wu;Yisen Wang;Shu-Tao Xia;James Bailey

171
Citations

Frequent Co-Authors

Kotagiri Ramamohanarao University of Melbourne

Christopher Leckie University of Melbourne

Wassim M. Haddad Georgia Institute of Technology

Gregor Kennedy University of Melbourne

Lars Kulik University of Melbourne

Guozhu Dong Wright State University

Peter J. Stuckey Monash University

Jian Pei Duke University

Wei Liu University of Technology Sydney

François Bry Ludwig-Maximilians-Universität München

External Links

Personal website of James Bailey Google Scholar page

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