Research Interests & Collaborative Opportunities

Translational AI for healthcare, developed across technical, clinical, and patient-centred dimensions.

I focus on developing AI systems that are translatable in clinical practice. Thus, I collaborate across disciplines — clinicians, health economists, social scientists, HCI researchers, ethical scientists, and patients and end-users.

My research spans three interconnected themes described in detail below.

Technical Advancements
Technical Advancements
Multimodal learning with explainability and interpretability as a central concern. More recently focused on mitigating hallucinations in LLMs and grounding their knowledge in clinical evidence and guidelines.
Human Activity Recognition · Vision-Language Models · Foundation Models & Agentic Systems · Interpretable Concept-Based Learning
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Healthcare Domains
Healthcare Domains
Translational AI developed closely with clinical domain experts. Four active research pillars — neurology, dermatology, histopathology, and hospital settings — with expanding interests in cardiology and human kinetics.
Neurology (Epilepsy, Stroke, Parkinson’s, MS) · Dermatology · Histopathology · Hospital Settings
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Patient & Clinician-Centred Design
Patient & Clinician-Centred Design
Collaborations with social scientists and patient/community organisations to co-design AI systems that are genuinely acceptable and adaptable in practice — not limited to just research.
Co-design · Adoption · Ethics · HCI · End-user Perspectives
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I am always looking for collaborations from diverse disciplines who are genuinely committed to building translatable AI systems for healthcare. Please reach out if interested.