Aris Alissandrakis
University of Hertfordshire, Linnaeus University, Tokyo Institute of Technology
Papers
24
Total Citations
669
H-Index
13
About
Aris Alissandrakis is a prominent researcher in robotics, artificial intelligence, and human-robot interaction, whose work has fundamentally shaped our understanding of how robots can learn from and interact with humans and other agents. His most significant contributions center on robotic imitation — particularly the challenging "correspondence problem," which addresses how robots with different body structures can meaningfully replicate actions demonstrated by humans or other robots. His landmark paper *Imitation with ALICE* (2002, 131 citations) and the co-edited volume *Imitation and Social Learning in Robots, Humans and Animals* (2007, 132 citations) established him as a leading voice bridging robotics, cognitive science, and animal behavior. His formalization of body mapping through correspondence metrics provided researchers with rigorous mathematical tools for cross-embodiment imitation. Beyond theoretical contributions, Alissandrakis has explored practical applications including programming robots through demonstration, domestic task learning, and playful human-robot interaction with humanoid platforms. His work on gesture recognition and motion-based play interactions reflects a broader vision of robots as social companions in everyday environments. Collectively, his research has garnered over 500 citations, reflecting sustained influence across robotics, AI, and the cognitive sciences.
Research Focus
Key Achievements
Top Papers
- 1Imitation and Social Learning in Robots, Humans and Animals132 citations · 2007
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- 4Self-Imitation and Environmental Scaffolding for Robot Teaching44 citations · 2007
- 5Action, State and Effect Metrics for Robot Imitation32 citations · 2006
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- 7Towards robot cultures?26 citations · 2004
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- 10Human to robot demonstrations of routine home tasks22 citations · 2008