Associate ProfessorSamaneh Madanian

Dr Samaneh (Sam) Madanian is an Associate Professor and co-director of the AUT Institute of Biomedical Technologies. She is an internationally recognised researcher in AI-driven digital health and health data science. Her expertise lies in developing intelligent systems that integrate artificial intelligence, data science, the Internet of Things (IoT), and computational health analytics to support clinical decision-making, public health surveillance, and healthcare system transformation. She is particularly interested in addressing complex healthcare challenges in neurological disorders, mental health monitoring, and disaster health management.

Dr Madanian has an interdisciplinary background spanning information technology, project management, and solution architecture, combined with industry experience as a business analyst and project manager before entering academia. This combination enables her to develop research that bridges advanced computational methods with real-world healthcare implementation. She is a Fellow of the Australasian Institute of Digital Health (FAIDH), the peak professional body for digital health in Australasia. She has been invited to serve on grant assessment committees for AI and digital health initiatives in New Zealand, Australia, Canada, and Switzerland, showcasing her knowledge, contributions, and leadership in this field. She has been interviewed by RNZ on AI Usage in Healthcare and the requirements of having clear law, and AI for Brain Health, and served as a panellist at the University of Melbourne Future Careers Forum Online: AI Revolution, highlighting the societal relevance and public impact of her research. 

Dr Madanian’s research has been published in leading digital health, AI and Health AI journals, including Nature Scientific Reports, JMIR journals, IEEE biomedical venues, and other high-impact outlets. She is a regular member of Program and Organising Committees related to Digital Health and Health AI research. Dr Madanian leads research at the intersection of AI, digital health technologies, and healthcare system innovation, focusing on scalable solutions that improve healthcare access, safety, and equity. She currently supervises multiple PhD and master's researchers working on AI applications in healthcare. Her research contributes to the global shift toward data-driven, predictive, and personalised intelligent healthcare systems. Her work particularly emphasises:

- AI-enabled clinical decision support

- Speech and behavioural analytics for neurological and mental health detection

- Healthcare digital twins system

- Mental Health Technologies and Computational Psychiatry

- IoT-based patient monitoring systems

- AI-driven public health surveillance

- Digital health systems for disaster and emergency contexts

Dr Madanian welcomes PhD and Master's students interested in these interdisciplinary research areas. 

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Current research studies and supervision:

Primary Supervision

• Clinically Informed Speech Profiling via AI-Based Segmentation to Support mTBI Assessment (Fredy Rojas, 2024 - Present) - PhD
• An Integrated Framework for Risk Stratification in New Zealand Emergency Departments using ML (Hamidreza Rasouli Panah, 2022–present) – PhD
• Audio Analysis for Healthcare Applications: mTBI Case Study (Upeka DeSilva, 2022–present) – PhD
• Computer Vision Applications in Healthcare for Patient Safety (Nam Hoang Nguyen, 2022–present) – PhD

• Biomedical Data Integration Framework for Glucose Level Prediction Using ML  (Haider Ali, 2021–2025) – PhD
• Towards Self-Healing Networks: AI-Based Log Analytics and Automated Remediation (Chengwei Feng, 2025-2026)
• AI-Enabled Clinical Decision Support for Oral Disease Detection (Priyadarshini Natarajan, 2023-2025) - Master's by Research 
• Speech Analysis as a Decision Support System in Healthcare for Detecting Mild Traumatic Brain Injury (Hoang Minh Quach, 2022-2024) - Master's by Research
• Performance Evaluation of Lightweight Cryptographic Algorithms for IoT in Healthcare (Tserendorj Chinbat, 2021-2023) - Master's by Research
• IoT and RFID Applications in Pandemic Management (Mohammad Elvan Nazayer, 2020-2022) - Master's by Research

Co-Supervised Research

• The Vital Compass: Exploring Digital Transformation in Government Organisations (2024–present) – PhD
• Unravelling the Impact of Mutations on Protein Structures Using Graph Neural Networks (2024–present) – PhD
• Developing an Agile Maturity Model for Government Institutions: A Case Study from Indonesia (2024–present) – PhD
• IoT-Based System for Depression Well-being Monitoring (2022–present) – PhD
• Real-Time Digital Twins for Renewable Energy Farms (2021–present) – PhD
• Stock Market Prediction Using Generative AI, Graph Neural Networks, and Cloud Computing (2024–present) – Master's Thesis