Humans stand to benefit tremendously from the acceleration of developments in computing and AI. In this context, we recognize both the importance and limitations of the humans-in- the-loop. On one side, the training, design, and instructions from humans is a critical need for effective computing and AI. On the other side, humans are limited by their cognition, perceptual, and physical abilities. To address this duality, we envision an approach of amplifying intelligence, by designing for human interaction across the entire human-to-computing continuum. In this approach, human expertise, intent, and limitations are each factored into all parts of the computational stack.
Next-generation interaction requires innovative human-computing architectures, fostering collaboration and co-design for seamless integration into human workflows.
Exploring the nexus of Attention, Explainability, and Expertise Amplification in AI systems, with a focus on optimizing outputs for human decision-making.
Exploring the integration of physical and digital realms, we aim to harness augmented, virtual, and mixed reality to weave a digitally-enriched narrative of the real world.
Navigating the landscape of human-computer interaction, our focus extends to multi-sensor architectures, utilizing computer vision and diverse sensing techniques to understand both human intent and state.
