Mathew Marge
Papers
1
Total Citations
4
H-Index
1
About
Mathew Marge is a leading researcher in human-robot interaction, with a focus on how robots can understand and respond to people through multiple communication modalities. His work sits at the intersection of machine learning, dialogue systems, and multimodal interaction, exploring how robots can coordinate speech, gestures, and vision to communicate more naturally with humans. In his influential special issue introduction on machine learning for multimodal interactive systems, he helped define the emerging research agenda for building robots that can process and integrate diverse input streams—such as audio, visual cues, and physical actions—in real time. This foundational work has shaped how researchers approach the design of socially aware robots that can collaborate with people in dynamic environments. While his most-cited paper has garnered 4 citations, its conceptual impact extends beyond raw numbers, influencing subsequent studies on multimodal dialogue and embodied interaction. Marge's contributions are particularly valuable for students and engineers working on next-generation robotic assistants that must navigate the complexity of human communication across sight, sound, and motion.
Research Focus
Key Achievements
Top Papers
- 1