What we study

Research

We develop computational and engineering approaches that connect biological mechanisms and physiological measurements with clinically useful decisions.

Better measurements brighter care
Research areas
01

AI and Physiological Data

Interpretable methods for ventilator waveforms, ECG, imaging and other clinical signals.

Machine learning Deep Learning Signal Processing Medical imaging Explainable AI
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02

Disease Progression and Prediction

Longitudinal models that connect patient trajectories with clinically useful risk estimates.

Disease modelling Risk prediction Network analysis Mathematical modelling Precision medicine
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03

Medical Devices and Respiratory Sensing

Affordable systems for physiological measurement, respiratory assessment and critical-care data acquisition.

CAD designing Simulation and modelling Indigenous medical devices Prototyping Data visualization Data acquisition
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04

Mechanistic and Synthetic Biology

Dynamical and biomolecular models used to understand disease mechanisms and design controllable biological systems.

Molecular biology DNA Nanotechnology Gene regulation Synthetic circuits Biosensing Cell free system
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Our approach

How projects progress

Each project is designed around a transparent path from clinical need to evaluation.

01

Clinical need

We start with a real, well-defined healthcare problem.

02

Measurement and data

We collect or use relevant physiological and clinical data.

03

Model or device

We develop computational models or physical devices.

04

Technical validation

We test performance with rigorous technical evaluation.

05

Clinical translation

We work towards real-world deployment and clinical impact.