Emmanuel Ferreira
Papers
3
Total Citations
70
H-Index
3
About
Emmanuel Ferreira is a leading researcher at the intersection of artificial intelligence, human-robot interaction, and dialogue systems. His work focuses on developing socially intelligent robots capable of natural, adaptive conversations with humans. Ferreira’s major contribution lies in pioneering reinforcement-learning-based dialogue management for situated human-robot interactions, where he introduced socially-inspired reward functions that enable robots to learn optimal conversational strategies through trial and error. His most cited paper (2015, 51 citations) demonstrates how reinforcement learning can train dialogue systems to respond not just with factual accuracy but with social appropriateness, making interactions more engaging and human-like. He further advanced the field by simulating human-robot interactions for dialogue strategy learning (10 citations) and by modeling users’ belief awareness in situated dialogue management (9 citations), allowing robots to track and adapt to what users know during conversations. Ferreira’s work bridges machine learning and social robotics, providing foundational frameworks for creating robots that understand context, maintain coherent dialogues, and respond empathetically. His research has significant implications for assistive robotics, customer service automation, and educational technologies, establishing him as a key contributor to the development of socially aware conversational agents.
Research Focus
Key Achievements
Top Papers
- 1
- 2Simulating Human-Robot Interactions for Dialogue Strategy Learning10 citations · 2014
- 3