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Alan Wang

Associate Professor

Organisation :

University of Auckland

Sector:

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Location:

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Biography

Associate Professor Alan Wang is a principal investigator at the Auckland Bioengineering Institute, Centre for Brain Research, and Medical Imaging Research Centre at the University of Auckland. He is also Theme Lead for Technology, Engineering and the Digital Economy at CCREATE-AGE, the University’s Co-Created Ageing Research Centre. He leads interdisciplinary research in AI-enabled medical imaging, computational neuroscience, intelligent rehabilitation, and healthy ageing. His work develops clinically relevant methods for disease detection, image quantification, outcome prediction, and personalised care, particularly in stroke, neurological disorders, cancer, and ageing. He collaborates with clinicians, engineers, communities, and industry to translate multimodal imaging, biosignals, digital health, and AI into practical and equitable healthcare tools.

Research Projects and Ideas

Current projects include multimodal AI for predicting stroke recovery; federated stroke-lesion segmentation; AR- and AI-supported neurorehabilitation; AI-guided medical imaging for cancer detection and treatment; imaging biomarkers for neurological disorders; and intelligent technologies for healthy ageing. The programme spans model development, clinical validation, and responsible implementation.

Collaborations and Skills

Our team offers expertise in medical image analysis, machine learning, multimodal MRI, CT and EEG, segmentation, prediction modelling, federated learning, AR rehabilitation, and clinical validation. We welcome partnerships with hospitals, Māori and community health organisations, researchers, and industry to co-design studies, validate AI tools, and translate prototypes into clinical practice.

Connections of interest

Interested in connecting with clinicians, health services, Māori and Pacific health partners, AI and imaging researchers, rehabilitation specialists, data custodians, policymakers, and medtech companies. Key interests include multi-site validation, responsible data sharing, equitable AI, co-designed clinical studies, student supervision, and national and international funding collaborations.

Speciality(s)

AI Speciality(s):

Agentic AI & Autonomous Systems

Explainable AI & Interpretability

Machine Learning

Natural Language Processing & Large Language Models

AI Education

Generative AI

Medical Imaging

Wearables

Research Expertise:

Health Speciality(s):

Mental Health

Oncology

Paediatrics & Child Health

Rehabilitation & Physical Therapy

Neurology & Neuroscience

Orthopaedics

Radiology & Medical Imaging

Surgery & Interventional

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