Bidirectional Interaction

Bidirectional interaction research explores systems where two entities mutually influence each other, going beyond simple one-way feedback. Current work focuses on developing models and algorithms that enable this reciprocal exchange, encompassing areas like human-computer interaction (e.g., using AR to link virtual and physical sketches), educational technology (e.g., leveraging LLMs for student-driven questioning), and physical systems (e.g., analyzing computation-dissipation trade-offs in mesoscopic devices). This research is significant for advancing AI capabilities, improving human-computer interfaces, and enhancing our understanding of complex systems by enabling more nuanced and effective interactions.