• What if your ears could become a window into your cardiovascular health? What if a child’s first encounter with AI didn’t come from YouTube, but from building and training their own models in the classroom? What if a $10 camera could detect industrial faults in milliseconds—without touching the cloud? This talk explores the reality of Edge AI at human scale: intelligent systems engineered to operate entirely on-device, under real-world constraints. OmniBuds is a clinically driven, ear-worn digital health platform that enables continuous, passive, and context-aware monitoring of hypertension and respiratory health, using multimodal sensing and microcontroller-optimised inference. Bella is a foundational AI education platform that introduces computing and artificial intelligence to children aged 6–12 through interactive, explainable, and offline model training—crafted specifically for safety, engagement, and accessibility in diverse classroom environments. CaaS is an edge-native camera platform for industrial automation, delivering low-latency, task-specific visual intelligence on low-power microcontrollers, without relying on external compute or connectivity. These platforms required targeted innovations in few-shot learning, self-supervised techniques, compiler-level optimisation, and event-driven inference—all while balancing efficiency, interpretability, and real-world resilience. I will conclude by outlining core principles for translating AI research into deployable, trustworthy, and domain-specific systems that scale—advancing the vision of pervasive intelligence across health, education, and industry.

  • Wearable neural interfaces are emerging as a transformative technology for human-machine interaction, yet bandwidth, comfort, and energy efficiency limitations constrain current solutions. This keynote introduces the pioneering work of Neuranics Limited, a deep-tech spinout from the Universities of Glasgow and Edinburgh, which is developing the world’s most sensitive Tunnel MagnetoResistance (TMR)-based magnetic sensors for seamless neural interfacing. The lecture explores Neuranics’ end-to-end sensor solution, integrating ultra-sensitive TMR sensors and custom low-power microelectronics design. It will further provide insights into sensor design innovations, scalable semiconductor manufacturing, and biosignal measurements using compact, wearable devices. We highlight the company’s scalable semiconductor fabrication processes, expanding patent portfolio, performance benchmarks, and real-world applications in magnetomyography (MMG) and magnetocardiography (MCG). This keynote offers a forward-looking perspective on how magnetic sensing is poised to redefine the landscape of semiconductor design for bioelectronics and XR hardware.

  • An engineer’s perspective on some key break throughs in the field of time-of-flight sensing, that helped turn a side project into a ubiquitous technology and multi-billion dollar commercial success.