Development of multiferroics, electronic materials, twistronics, 2D materials, synaptic devices, emerging volatile and non-volatile memory technologies, and neuromorphic integrated circuits for energy-efficient computing and sensing.

Mathematical and computational models that describe how neuronal populations encode information, adapt to changing environments, and generate complex behaviours.

Advanced methods for recording, analysing, and interpreting neural activity using AI and machine-learning techniques for applications in neuroscience and medicine.

Flexible and bioelectronic interfaces that enable long-term communication between neural tissue and electronic systems while ensuring safety and biocompatibility.

Brain-inspired hardware architectures capable of adaptive learning, real-time processing, and energy-efficient artificial intelligence.

Integrated systems that continuously monitor neural activity, interpret brain signals, and deliver personalised therapeutic or assistive interventions.

Evaluation of neuromorphic technologies using clinical data, ethical frameworks, and translational pathways toward future healthcare applications.