Refereed Journal Publications

Journal articles are listed in reverse chronological order where possible. Links point to public DOI, publisher, arXiv, institutional repository, or project pages where available.

1. A Survey on the Use of Machine Learning within Computer Algebra

   Uzma Shafiq, Matthew England, and Nayyar Zaidi.

   ACM Computing Surveys, online first, 2026.

   DOI

2. Towards Building Robust Models for Unimodal and Multimodal Medical Imaging Data

   Joy Dhar, Puneet Goyal, Maryam Haghighat, Nayyar Zaidi, Ferdous Sohel, Quoc Bao Vo, and K. C. Santosh.

   Information Fusion, 127, Part C, Article 103822, 2026.

   DOI ScienceDirect

3. Ensembled Bayesian Tabular Data Generator

   Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, Gang Li, and Wray Buntine.

   Knowledge and Information Systems, 68(1), Article 36, 2026.

   DOI Publication page

4. Improving Fire and Smoke Detection Using YOLO with Ghost Convolutions, Bidirectional Feature Pyramid Networks, and Image Enhancement

   Christine Dewi, Dhananjay Thiruvady, Stephen Abednego Philemon, and Nayyar Zaidi.

   Engineering Applications of Artificial Intelligence, 178, Part 2, Article 115116, 2026.

   DOI ScienceDirect

5. Knowledge-Guided Object Detection via Bayesian Networks and Knowledge Graphs (KGBNCNet)

   Christine Dewi, Rasoul Amirzadeh, Dhananjay Thiruvady, and Nayyar Zaidi.

   Expert Systems with Applications, 297, Part B, Article 129385, 2026.

   DOI ScienceDirect

6. Effective Interpretable Learning for Large-Scale Categorical Data

   Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, Tao Wang, and Gang Li.

   Data Mining and Knowledge Discovery, 38, 2223–2251, 2024.

   DOI Springer

7. Adaptive Population-Based Simulated Annealing for Resource-Constrained Job Scheduling with Uncertainty

   Dhananjay Thiruvady, Su Nguyen, Yi Sun, Fatemeh Shiri, Nayyar Zaidi, and Xiaodong Li.

   International Journal of Production Research, 62(17), 6227–6250, 2024.

   DOI Taylor & Francis

8. Robust Visual Question Answering via Semantic Cross-Modal Augmentation

   Akib Mashrur, Wei Luo, Nayyar Zaidi, and Antonio Robles-Kelly.

   Computer Vision and Image Understanding, 238, Article 103862, 2024.

   DOI ScienceDirect Deakin DRO

9. Aspect-Based Automated Evaluation of Dialogues

   Arash Shabanpour, Ziwei Hou, Muhammad Akbar Husnoo, Khanh Linh Nguyen, John Yearwood, and Nayyar Zaidi.

   Knowledge-Based Systems, 279, Article 110901, 2023.

   DOI ScienceDirect Deakin DRO

10. Property Graph Representation Learning for Node Classification

    Shu Li, Nayyar Zaidi, Meijie Du, Zhou Zhou, Hongfei Zhang, and Gang Li.

    Knowledge and Information Systems, 66(1), 237–265, 2024.

    DOI Springer

11. Improving Neural Network’s Robustness on Tabular Data with D-Layers

    Haiyang Xia, Nayyar Zaidi, Yishuo Zhang, and Gang Li.

    Data Mining and Knowledge Discovery, 38(1), 173–205, 2024.

    DOI Springer Deakin DRO

12. Interpretable Tabular Data Generation

    Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, and Gang Li.

    Knowledge and Information Systems, 65, 2935–2963, 2023.

    DOI Springer

13. On the Use of Machine Learning Methods in Rock Art Research with Application to Automatic Painted Rock Art Identification

    Andrea Jalandoni, Yishuo Zhang, and Nayyar Zaidi.

    Journal of Archaeological Science, 144, Article 105629, 2022.

    DOI ScienceDirect Deakin DRO

14. Surrogate-Assisted Population-Based ACO for Resource-Constrained Job Scheduling with Uncertainty

    Dhananjay Thiruvady, Su Nguyen, Fatemeh Shiri, Nayyar Zaidi, and Xiaodong Li.

    Swarm and Evolutionary Computation, 69, Article 101029, 2022.

    DOI ScienceDirect Publication page

15. Machine Learning for Financial Risk Management: A Survey

    Akib Mashrur, Wei Luo, Nayyar Zaidi, and Antonio Robles-Kelly.

    IEEE Access, 8, 203203–203223, 2020.

    DOI IEEE Xplore Deakin DRO

16. On the Effectiveness of Discretizing Quantitative Attributes in Linear Classifiers

    Nayyar Zaidi, Yang Du, and Geoffrey I. Webb.

    IEEE Access, 8, 198856–198871, 2020.

    DOI IEEE Xplore arXiv Deakin DRO

17. Proximity Forest: An Effective and Scalable Distance-Based Classifier for Time Series

    Benjamin Lucas, Ahmed Shifaz, Charlotte Pelletier, Lachlan O’Neill, Nayyar Zaidi, Bart Goethals, François Petitjean, and Geoffrey I. Webb.

    Data Mining and Knowledge Discovery, 33(3), 607–635, 2019.

    DOI arXiv Deakin DRO

18. Accurate Parameter Estimation for Bayesian Network Classifiers Using Hierarchical Dirichlet Processes

    François Petitjean, Wray Buntine, Geoffrey I. Webb, and Nayyar Zaidi.

    Machine Learning, 107(8–10), 1303–1331, 2018.

    DOI arXiv Code

19. Efficient Parameter Learning of Bayesian Network Classifiers

    Nayyar Zaidi, Geoffrey I. Webb, Mark Carman, François Petitjean, Wray Buntine, M. Hynes, and H. De Sterck.

    Machine Learning, 106(9–10), 1289–1329, 2017.

    DOI Code

20. ALRⁿ: Accelerated Higher-Order Logistic Regression

    Nayyar Zaidi, Geoffrey I. Webb, Mark Carman, François Petitjean, and Jordi Cerquides.

    Machine Learning, 104(2–3), 151–194, 2016.

    DOI Code

21. Scalable Learning of Bayesian Network Classifiers

    Amanda Martinez, Geoffrey I. Webb, Shenglei Chen, and Nayyar Zaidi.

    Journal of Machine Learning Research, 17(44), 1–35, 2016.

    JMLR page PDF

22. Alleviating Naive Bayes Attribute Independence Assumption by Attribute Weighting

    Nayyar Zaidi, Jordi Cerquides, Mark Carman, and Geoffrey I. Webb.

    Journal of Machine Learning Research, 14(24), 1947–1988, 2013.

    JMLR page PDF

Refereed Conference Publications

Conference papers are listed in reverse chronological order where possible. Accepted or forthcoming papers without stable public pages are marked as link forthcoming.

1. HiGMR-Net: Hierarchical Graph Memory Refinement Network for Multi-View EEG Connectivity Sequence Learning

   Debashis Das Chakladar, Ikbeom Jan, Adeel Razi, Debora Christina Muchaluat-Saade, Nayyar Zaidi.

   Proceedings of the ACM International Conference on Multimedia (ACM MM), accepted, 2026.

   Link forthcoming

2. Feature-Engineered Reinforcement Learning for S-Pair Selection in Buchberger’s Algorithm

   Uzma Shafiq, Matthew England, Nayyar Zaidi.

   Proceedings of the UK Workshop on Computational Intelligence (UKCI), accepted, 2026.

   Link forthcoming

3. KITDG: Knowledge-Infused Tabular Data Generation

   Daniel EE Gan, Nayyar Zaidi, Son Tran.

   Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), accepted, 2026.

   Link forthcoming

4. HyPCA-Net: Advancing Multimodal Fusion in Medical Image Analysis

   Joy Dhar, Manish Kumar Pandey, Debashis Das Chakladar, Maryam Haghighat, Azadeh Alavi, Sajib Mistry, and Nayyar Zaidi.

   Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 1831–1840, 2026.

   PDF WACV page

5. Effective and Robust Multimodal Medical Image Analysis

   Joy Dhar, Nayyar Zaidi, and Maryam Haghighat.

   Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), accepted, 2026.

   DOI DBLP

6. Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention

   Joy Dhar, Manish Kumar Pandey, Nayyar Zaidi, Chen Chen, Maryam Haghighat, Ferdous Sohel, and Puneet Goyal.

   Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), accepted, 2026.

   arXiv Code

7. Does a Hybrid Space-Aware Randomized Defense Improve Empirical and Certified Adversarial Robustness?

   Joy Dhar, Manish Kumar Pandey, Behzad Bozorgtabar, Nayyar Zaidi, Wenyu Zhang, Wei-Hong Li, Tingting Mu, Dwarikanath Mahapatra, Mahsa Baktashmotlagh, Trung Le, Chen Chen, Sajib Mistry, Camila Gonzalez, Samira Ebrahimi Kahou, Lina Yao, Piotr Koniusz, Robert Burns Fisher, Dinh Phung, Bohyung Han, Nuno Vasconcelos, and Pietro Liò.

   Proceedings of the 43rd International Conference on Machine Learning (ICML), Proceedings of Machine Learning Research, vol. 306, accepted, 2026.

   Publication listing

8. Certified vs. Empirical Adversarial Robustness via Hybrid Convolutions with Attention Stochasticity

   Joy Dhar, Song Xia, Manish Kumar Pandey, Maryam Haghighat, Azadeh Alavi, Ferdous Sohel, Wenyu Zhang, and Nayyar Zaidi.

   Proceedings of the International Conference on Learning Representations (ICLR), 2026.

   ICLR page PDF arXiv

9. KGGAT: Knowledge-Guided Graph Attention Network for Multi-Label Image Classification

   Christine Dewi, Dhananjay R. Thiruvady, and Nayyar Zaidi.

   Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Findings (CVPR Findings), pp. 8766–8775, 2026.

   CVF page PDF Code

10. Knowledge-Guided Graph Convolutional Network for Multi-Label Image Classification

    Christine Dewi, Dhananjay Thiruvady, Stephen Abednego Philemon, and Nayyar Zaidi.

    Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), accepted, 2026.

    GitHub ICRA listing

11. One Credential, Many Journeys: Persona-Aligned Assessment for Postgraduate Microcredentials in Emerging Technologies

    Laura Tubino and Nayyar Zaidi.

    Proceedings of the Australasian Computing Education Conference (ACE), 2026.

    DOI ACM

12. Brain Connectivity Transformer: A Unified fMRI-Based Framework for Joint Cognitive Tasks and Disorder Classification

    Debashis Das Chakladar, K. H. Madsen, Dwarikanath Mahapatra, Nayyar Zaidi, M. J. Saikia, and V. Chang.

    Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), accepted, 2026.

    Link forthcoming

13. Letting Homogeneity Entropy Select S-Pairs in Buchberger’s Algorithm

    Uzma Shafiq, Matthew England, AmirHosein Sadeghimanesh, and Nayyar Zaidi.

    Proceedings of the International Workshop on Computer Algebra in Scientific Computing (CASC), Lecture Notes in Computer Science, pp. 273–290, 2026.

    DOI Publication page

14. Prompt and Probe: Data-Efficient Adaptation of Black-Box Foundation Models via Unified Active Visual Prompting

    Dwarikanath Mahapatra, Abhijit Das, Sudipta Roy, Manish Pandey, Joy Dhar, Nayyar Zaidi, Zongyuan Ge, Behzad Bozorgtabar, Mauricio Reyes, and Imran Razzak.

    Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), accepted, 2026.

    Publication listing

15. Multimodal Fusion Learning with Dual Attention for Medical Imaging

    Joy Dhar, Nayyar Zaidi, Maryam Haghighat, Sudipta Roy, Puneet Goyal, Azadeh Alavi, and Vikas Kumar.

    Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 4362–4371, 2025.

    CVF page PDF arXiv

16. Aspect-Based Fake News Detection

    Ziwei Hou, Bahadorreza Ofoghi, Nayyar Zaidi, and John Yearwood.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Part VI, pp. 95–107, 2024.

    Springer DBLP

17. MEG: Masked Ensemble Tabular Data Generator

    Yishuo Zhang, Nayyar Zaidi, Gang Li, and Wray Buntine.

    Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 838–847, 2023.

    DOI Deakin DRO

18. Robust Quantification of Prediction Uncertainty by Inducing Heterogeneity in Deep Ensembles

    Akib Mashrur, Wei Luo, Nayyar Zaidi, and Antonio Robles-Kelly.

    Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 478–485, 2023.

    DOI DBLP

19. Kernel-Based Feature Extraction for Time Series Clustering

    Yuhang Liu, Yishuo Zhang, Yang Cao, Ye Zhu, Nayyar Zaidi, C. Ranaweera, Gang Li, and Q. Zhu.

    Proceedings of the International Conference on Knowledge Science, Engineering and Management (KSEM), Part I, pp. 276–283, 2023.

    Springer DOI

20. Advancing Text Summarization Through the Utilization of Arbitrary Aspect Learning

    Ziwei Hou, Bahadorreza Ofoghi, Nayyar Zaidi, Mahmood Mammadov, S. Huda, and John Yearwood.

    Proceedings of the International Conference on Modeling Decisions for Artificial Intelligence (MDAI), 2023.

    Deakin DRO

21. Leveraging Generative Models for Combating Adversarial Attacks on Tabular Datasets

    Jiahui Zhou, Nayyar Zaidi, Yishuo Zhang, Paul Montague, Junae Kim, and Gang Li.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Part I, pp. 147–158, 2023.

    Springer DOI

22. Novel-Domain Object Segmentation via Reliability-Aware Teacher Ensemble

    M. Jing, Wei Luo, Nayyar Zaidi, and J. Wang.

    Proceedings of the IEEE International Conference on High Performance Computing and Communications (HPCC), pp. 761–768, 2022.

    DOI Publication page

23. Semantic Multi-Modal Reprojection for Robust Visual Question Answering

    Akib Mashrur, Wei Luo, Nayyar Zaidi, and Antonio Robles-Kelly.

    Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 1–6, 2022.

    DOI IEEE Xplore Deakin DRO

24. Discretization-Inspired Defence Algorithm Against Adversarial Attacks on Tabular Data

    Jiahui Zhou, Nayyar Zaidi, Yishuo Zhang, and Gang Li.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 367–379, 2022.

    DOI Springer

25. GANBLR++: Incorporating Capacity to Generate Numeric Attributes and Leveraging Unrestricted Bayesian Networks

    Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, and Gang Li.

    Proceedings of the SIAM International Conference on Data Mining (SDM), pp. 298–306, 2022.

    DOI SIAM Deakin DRO

26. GANBLR: A Tabular Data Generation Model

    Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, and Gang Li.

    Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 181–190, 2021.

    DOI Deakin DRO Software

27. Robust Neural Regression via Uncertainty Learning

    Akib Mashrur, Wei Luo, Nayyar Zaidi, and Antonio Robles-Kelly.

    Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 1–6, 2021.

    DOI arXiv Deakin DRO

28. Neighbours and Kinsmen: Hateful Users Detection with Graph Neural Network

    Shu Li, Nayyar Zaidi, Qi Liu, and Gang Li.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2021.

    PDF

29. Efficient and Effective Accelerated Hierarchical Higher-Order Logistic Regression for Large Data Quantities

    Nayyar Zaidi, François Petitjean, and Geoffrey I. Webb.

    Proceedings of the SIAM International Conference on Data Mining (SDM), pp. 459–467, 2018.

    DOI Deakin DRO

30. A Fast Trust-Region Newton Method for Softmax Logistic Regression

    Nayyar Zaidi and Geoffrey I. Webb.

    Proceedings of the SIAM International Conference on Data Mining (SDM), pp. 705–713, 2017.

    DOI Deakin DRO

31. Artificial Neural Network: Deep or Broad? An Empirical Study

    Nian Liu and Nayyar Zaidi.

    Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), Lecture Notes in Computer Science, vol. 9992, pp. 535–541, 2016.

    DOI Publication page

32. Preconditioning an Artificial Neural Network Using Naive Bayes

    Nayyar Zaidi, François Petitjean, and Geoffrey I. Webb.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Part I, Lecture Notes in Computer Science, vol. 9651, pp. 341–353, 2016.

    DOI Publication page

33. Naive-Bayes Inspired Effective Pre-Conditioners for Speeding-Up Logistic Regression

    Nayyar Zaidi, Mark Carman, Jordi Cerquides, and Geoffrey I. Webb.

    Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 1097–1102, 2014.

    DOI

34. Fast and Efficient Single-Pass Bayesian Learning

    Nayyar Zaidi and Geoffrey I. Webb.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 149–160, 2012.

    DOI Deakin DRO

35. Local Adaptive SVM for Object Recognition

    Nayyar Zaidi and David McGregor Squire.

    Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 196–201, 2010.

    DOI Deakin DRO

36. A Gradient-Based Metric Learning Algorithm for k-NN Classifiers

    Nayyar Zaidi, David McGregor Squire, and David Suter.

    Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), Lecture Notes in Computer Science, vol. 6464, pp. 194–203, 2010.

    DOI Publication page

37. SVMs and Data-Dependent Distance Metric

    Nayyar Zaidi and David McGregor Squire.

    Proceedings of the International Conference of Image and Vision Computing New Zealand (IVCNZ), Article 6148826, 2010.

    DOI Publication page

38. BoostML: An Adaptive Metric Learning for Nearest Neighbor Classification

    Nayyar Zaidi, David McGregor Squire, and David Suter.

    Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 142–149, 2010.

    DOI

39. Database Normalization as a By-Product of Minimum Message Length Inference

    David L. Dowe and Nayyar Zaidi.

    Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), Lecture Notes in Computer Science, vol. 6464, pp. 82–91, 2010.

    DOI Springer

40. Confidence-Rated Boosting Algorithm for Generic Object Detection

    Nayyar Zaidi and David Suter.

    Proceedings of the International Conference on Pattern Recognition (ICPR), pp. 1–4, 2008.

    DOI Publication page

41. Object Detection Using a Cascade of Classifiers

    Nayyar Zaidi and David Suter.

    Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 600–605, 2008.

    DOI Publication page

Tutorials

Invited and peer-reviewed tutorials delivered at major international data mining conferences.

1. Recent and Emerging Trends in Tabular Data Generation

   Nayyar Zaidi, Yishuo Zhang, and Gang Li.

   Tutorial, IEEE International Conference on Data Mining (ICDM), 2022.

   Slides Official page

2. Harnessing the Power of Generative Adversarial Networks Style Learning for Tabular Data Generation

   Nayyar Zaidi, Yishuo Zhang, and Gang Li.

   Tutorial, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022.

   PAKDD page Tutorial page

Preprints

Manuscripts available as public preprints. Papers that have since appeared in refereed proceedings are listed under conference publications.

1. Fruit Classification System with Deep Learning and Neural Architecture Search

   Christine Dewi, Dhananjay Thiruvady, and Nayyar Zaidi.

   arXiv preprint, arXiv:2406.01869, 2024.

   arXiv DOI DBLP

2. On the Inter-Relationships Among Drift Rate, Forgetting Rate, Bias/Variance Profile and Error

   Nayyar Zaidi, Geoffrey I. Webb, François Petitjean, and Germain Forestier.

   arXiv preprint, arXiv:1801.09354, 2018.

   arXiv DOI Code

Technical Reports and Theses

1. A Simple Gradient-Based Metric Learning Algorithm for Object Recognition

   Nayyar Zaidi, D. Squire, and D. Suter.

   Technical Report 2010/256, Clayton School of IT, Monash University, 2010.

   PDF

2. Data-Dependent Distance Metric for Efficient Gaussian Process Classification

   Nayyar Zaidi and D. Squire.

   Technical Report, Clayton School of IT, Monash University, 2009.

   PDF

3. Metric Learning and Scale Estimation in High-Dimensional Machine Learning Problems with an Application to Generic Object Recognition

   Nayyar Zaidi.

   PhD thesis, 2011.

   PDF

4. Generic Object Recognition

   Nayyar Zaidi.

   BSc Honours thesis, 2005.

   Link forthcoming