About me
Computational pathology and multimodal medical AI
I am a Research Fellow in the Centre for Health Informatics at the Australian Institute of Health Innovation, Macquarie University. My research develops multimodal AI methods that integrate histopathology with molecular and clinical data for cancer diagnosis, prognosis, and treatment stratification.
I completed my PhD in Computer Science and Engineering at UNSW Sydney in January 2026, supervised by Professor Erik Meijering, Professor Anant Madabhushi, and Associate Professor Ewan Millar. My work spans histopathology image analysis, spatial transcriptomics, vision–language learning, and multimodal foundation models.
My previous research appointments include visiting roles at Georgia Tech and Emory University and the Technical University of Munich. I also contribute to teaching in artificial intelligence, computer vision, and deep learning at UNSW Sydney.
Research themes
- Computational pathology Data-efficient and generalisable learning methods for histopathology image analysis.
- Spatial and multimodal oncology Integrating tissue morphology, spatial transcriptomics, molecular measurements, and clinical data.
- Translational medical AI Clinically relevant models for cancer treatment stratification and genomics-based motor neurone disease research.
News
- Joined the Australian Institute of Health Innovation, Macquarie University, as a Research Fellow.
- Two spatial transcriptomics-guided pathology studies were accepted for presentation at the ASCO Annual Meeting 2026, including an oral presentation based on the CHAARTED clinical trial.
- Completed my PhD at UNSW Sydney. Thesis: Advancing Computational Pathology with Multimodal Deep Learning.
- Presented PathDFM: Pathology Distillation Foundation Model for Multi-Scale WSI Analysis at NeurIPS 2025 in San Diego.
- Visited the Technical University of Munich and delivered an invited seminar on multimodal pathology AI.
- Served as Workshop Chair at MVIPIT 2025 for Few-shot and Incremental Learning for Data-Efficient AI.
Earlier updates
- Appointed Postdoctoral Writing Fellow (research-only) at UNSW Sydney.
- Invited speaker at the Datasets through the Looking-Glass webinar, IT University of Copenhagen.
- Recognised by ScholarGPS as a Highly Ranked Scholar (Prior Five Years) in Histopathology.
- Received the Arc PGC Research Candidate Award from the UNSW Postgraduate Council.
- Completed a visiting fellowship at the Madabhushi Lab, Georgia Tech and Emory University.
- Selected as a DAAD AInet Fellow (Postdoc-NeT-AI — AI for Science).
Selected publications
All publicationsLeveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images
IEEE Journal of Biomedical and Health Informatics, 2026
A vision–language approach to zero-shot histopathology image analysis.
Generalized Deep Learning for Histopathology Image Classification Using Supervised Contrastive Learning
Journal of Advanced Research, 2025
Supervised contrastive learning for generalisable histopathology classification.
Breast Cancer Histopathology Image-Based Gene Expression Prediction Using Spatial Transcriptomics Data and Deep Learning
Scientific Reports, 2023
Predicting breast-cancer gene expression from histopathology using spatial transcriptomics.
What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review
Artificial Intelligence Review, 2024
A comprehensive review of machine-vision methods for lymphatic histopathology.
Selected honours
- 2025
ScholarGPS Highly Ranked Scholar (Prior Five Years) in Histopathology.
- 2025
Arc PGC Research Candidate Award, UNSW Postgraduate Council.
- 2024
DAAD AInet Fellow, Postdoc-NeT-AI — AI for Science.
- 2022–2025
UNSW University International Postgraduate Award.
Work with me
Students and collaborators
I welcome enquiries from prospective PhD and MRes students, clinicians, researchers, and industry collaborators working in computational pathology, spatial and multimodal biomedical AI, precision oncology, or AI for motor neurone disease.