Generative Tabular Models
Synthetic data generation for structured tabular data, with emphasis on dependency modelling, fariness, privacy, data scarcity, and trustworthy generation.
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Computer Science · Data Science · Machine Learning
Nayyar Zaidi
Sr. Lecturer in Computer Science at Deakin University, Burwood, Australia.
As a machine learning and data science researcher, I am particularly interested in generative tabular models, knowledge-guided learning, multimodal learning, anomaly detection, scalable tabular classification, feature engineering, interpretable machine learning, and applied data science.
I lead the Data Mining and Knowledge Discovery Group, where we work on generative tabular models, knowledge-guided learning, knowledge-guided vision, multimodal learning, anomaly detection, and robust classification methods for structured data.
Research Focus
Knowledge-guided Learning
Machine learning methods that integrate domain knowledge, knowledge graphs, constraints, scientific principles, and expert structure.
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Multimodal Learning
Robust multimodal learning and fusion methods, particularly for medical image analysis and heterogeneous data sources.
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Anomaly Detection
Structure-aware and dependency-level anomaly detection for structured and heterogeneous tabular data.
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Tabular Classification
Classification methods for tabular data, including feature interactions, Bayesian network classifiers, causal learning, and few-pass learning.
Learn more »Recent Updates
- 2026: Two of our papers were accepted to the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), both as oral presentations. The papers are Effective and Robust Multimodal Medical Image Analysis and Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention.
- 2026: Our work on adversarial robustness, Certified vs. Empirical Adversarial Robustness via Hybrid Convolutions with Attention Stochasticity, was accepted to the International Conference on Learning Representations (ICLR).
- 2026: Our paper Does a Hybrid Space-Aware Randomized Defense Improve Empirical and Certified Adversarial Robustness? was accepted to the International Conference on Machine Learning (ICML).
- 2026: Our paper HiGMR-Net: Hierarchical Graph Memory Refinement Network for Multi-View EEG Connectivity Sequence Learning was accepted to the ACM International Conference on Multimedia (ACM MM), to be held in Rio de Janeiro, Brazil.
- 2026: Our first paper in Medical Image Computing and Computer Assisted Intervention (MICCAI), Prompt and Probe: Data-Efficient Adaptation of Black-Box Foundation Models via Unified Active Visual Prompting, was accepted.
- 2026: My student Uzma Shafiq’s survey paper, A Survey on the Use of Machine Learning within Computer Algebra, was accepted in ACM Computing Surveys.
- 2025: Our group was awarded an Alfred Deakin Postdoctoral Research Fellowship, with Dr Christine Dewi joining the DMKD Group as an Alfred Deakin Postdoctoral Research Fellow. Christine’s work strengthens our research in knowledge-guided learning and computer vision.
- July 2024: Started serving as an Associate Editor for Big Data Research.
- November 2023: Delivered an invited talk, Can We Trust Machine Learning Models?, at the Deakin Cyber Conference, Melbourne. [PDF]
- October 2023: Delivered an invited talk, Can We Trust Machine Learning Models? Who Watches the Watchers?, at the Australian Cyber Conference, Melbourne. CyberCon 2023
Prospective PhD Students
Scholarships at Deakin are limited and highly competitive. Many applicants have strong academic records and publications in leading venues. If you are interested in working with me, I recommend contacting me well before your intended start date.
Prospective students are encouraged to develop a clear research proposal aligned with one of my research areas. Strong preparation may include prior research experience, a relevant publication record, and evidence of technical depth in computer science, mathematics, engineering, data science, or a closely related discipline.
If you are interested in joining my group, please contact me with your CV, academic transcripts, publication list, and a brief statement of research interests. Students who already hold an externally funded scholarship are also welcome to contact me directly.
Available Positions
Current advertised PhD scholarship and position opportunities are listed below. This section will be updated when new funded PhD projects, scholarships, visiting positions, or research roles become available.
- Deakin RTP and DUPRS Scholarships: Main Deakin research scholarship page
In the News
Rock art detection
Professional Service
Editorial and journal service
- Associate Editor, Big Data Research
- Reviewer for journals including Data Mining and Knowledge Discovery, Machine Learning, Neural Networks, Neurocomputing, and Knowledge and Information Systems.
Conference service
- Organising Committee member, AJCAI 2022
- Program Committee member for venues including KDD, AAAI, ICDM, IJCAI, ACMMM, CIKM, ECML PKDD, PAKDD and AJCAI.