Timely Communication
Timely communication, encompassing efficient information exchange and coordinated action, is a crucial research area impacting diverse fields from AI to healthcare. Current research focuses on optimizing communication efficiency in distributed systems like federated learning, employing techniques such as scalar communication, zero-order optimization, and lossy compression to reduce bandwidth and energy consumption. This work also explores the development of robust communication strategies in noisy environments and the integration of AI, particularly LLMs, to enhance understanding and improve the efficiency of communication in various applications, including human-robot collaboration and crisis response. The resulting advancements have significant implications for improving the performance and scalability of AI systems, optimizing resource utilization in communication networks, and enhancing human-computer and human-robot interaction.
Papers
Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social Media
Julia Mendelsohn, Sayan Ghosh, David Jurgens, Ceren Budak
The Effect of Robot Skill Level and Communication in Rapid, Proximate Human-Robot Collaboration
Kin Man Lee, Arjun Krishna, Zulfiqar Zaidi, Rohan Paleja, Letian Chen, Erin Hedlund-Botti, Mariah Schrum, Matthew Gombolay