Toward Adaptive Physical Intelligence at the Human–Machine Interface

This talk explores the development of adaptive human-machine interfaces that combine bioelectronics, physiological sensing, artificial intelligence, and robotics to enable more seamless interactions between people and technology. Dr. Wu will present advances in wearable and wireless bioelectronic systems for monitoring physiological signals, including applications in brain activity, tissue health, and cognitive state assessment, as well as adaptive biointerfaces that improve communication between devices and the human body.

He will also discuss neuromuscular sensing technologies and machine-learning approaches that decode human movement and intent, linking neural activity to biomechanical performance. The talk concludes with bidirectional human-robot interaction systems that use these signals for intuitive robot control while providing tactile sensing and haptic feedback, illustrating a broader vision of human-machine systems that continuously adapt to users and their environments.