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Member Profiles List

Explore researchers, clinicians, and professionals shaping the future of AI in Health. Browse member profiles, discover areas of expertise, and connect with individuals across the network.

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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.

Alan Wang

Associate Professor

University of Auckland

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I’m a Research Data Specialist & Certified AI Specialist with 13+ years in the NZ health and research sector — transforming how data is captured, governed, and applied to drive real-world impact. From designing research data solutions to building ethical AI-powered automations, I combine technical expertise with a human-centered, problem-solving mindset to help teams work smarter, faster, and more efficiently. Core strengths: Data Management & Governance: accuracy, integrity, compliance Research & AI Solutions: practical systems, no-code AI tools, intelligent workflows Advanced Tools: Azure, Power BI, SQL, R, REDCap AI Entrepreneurship: leveraging AI to generate value, streamline processes, and unlock new opportunities I’m driven by curiosity, innovation, and impact — whether it’s shaping the future of ethical AI in research, automating repetitive workflows, or enabling smarter decisions with data.

Deepika Sonia

Research Data Specialist

Auckland University of Technology

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Catherine Shi is an AI and data science researcher at Auckland University of Technology (AUT). Her research focuses on designing computational approaches to make sense of complex, multimodal brain imaging data and apply AI to real health challenges. Catherine is deeply committed to collaborative, responsible innovation in health AI, and to fostering the cross-sector partnerships across academia, clinical practice, and industry that will be essential to realising AI's potential in healthcare.

Catherine Shi

Associate Professor

AUT

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I'm a medical doctor by background and currently work as a full-time academic at the Liggins Institute at the University of Auckland. I did my DPhil (PhD) at the University of Oxford on the use of mathematically modelling to improve the usability of digital health technologies such as EHRs and Clinical Decision Support systems. I'm the Editor-in-Chief of BMJ Digital Health & AI and the author of the "Textbook of Digital Health".

Chris Paton

Associate Professor in Health AI

University of Auckland

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Ryan P. Radecki MD MS FACEM FACEP is an emergency specialist in Waitaha Canterbury and a Clinical Informatics Director for Health New Zealand. His portfolio includes HealthX, the AI Lab, and the Centre for Digital Modernisation in Health.

Ryan Radecki

Emergency Medical Specialist / Clinical Informatics Director

Health New Zealand

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I specialise in utilising Operations Research (OR), Analytics and AI to work with communities and organisations in developing intelligent systems to support decision making. This approach translates across many application areas including Healthcare. I have developed models for providing OR, Analytics & AI for healthcare systems including data-driven optimised rosters for General Medicine, optimal rostering and dispatch for Patient Transit, and simulation and optimisation for Surgery Scheduling. I co-create platforms for integrating and analysing data to better understand systems using OR, Analytics & AI. The platforms empower decision makers with an accessible virtual sandpit, e.g., digital twin, to “play” with potential solutions and see evidence of solution outcomes. I am interested in research or consulting work on practical OR, Analytics & AI in collaboration with healthcare services, communities and government.

Mike O'Sullivan

Associate Professor/Deputy Director

University of Auckland/Te Pūnaha Matatini

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Daniel Wilson lectures in Computer Science at Waipapa Taumata Rau | University of Auckland. His teaching and research are in the areas of AI, Māori Data Sovereignty, Māori Algorithmic Sovereignty, and AI ethics. Daniel is a Co-Director of the Centre of Machine Learning for Social Good, Pou Pae Auaha at Ngā Pae o te Māramatanga, a member of Te Pokapū in The Māori Data Sovereignty Network - Te Mana Raraunga, member of the Kāhui Māori for the AI Forum, and treasurer of the AI Researchers Association. Daniel has a PhD in Philosophy and a Master of Professional Studies in Data Science from Waipapa Taumata Rau.

Daniel Wilson

Lecturer

Waipapa Taumata Rau | The University of Auckland

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Jerry was born in Taiwan and grew up in New Zealand. He first trained as a computer scientist and electrical engineer and worked as a web developer before moving towards teaching.  He was a primary teacher for 11 years in Taiwan. He then began his psychology career in Taiwan with a focus on the intersection between technology and people. Currently, he works as a senior lecturer at the University of Otago in the Department of Psychological Medicine. He also works as a clinical psychologist in private practice. Jerry's research interests include cognitive bias modification (CBM)—a digital self-administered intervention addressing unhelpful interpretation bias in various psychopathologies. Jerry has also applied CBM to other areas, including stereotype bias in medical students towards Māori patients.

Jerry Hsu

Clinical Psychologist and Lecturer

University of Otago

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I am a PhD candidate in Nursing at the University of Auckland. I previously completed a PhD in Health Education and Health Promotion. My background includes clinical practice, primary healthcare, health promotion, and research. My current research focuses on the use of artificial intelligence to support nurses in primary care, with a particular interest in AI-assisted tools that can reduce workload, improve clinical documentation, and enhance the quality of care for the community.

Atefeh Afshari

PhD candidate

School of Nursing, Faculty of Medical and Health Sciences, The University of Auckland

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