About

Stathis Kasderidis is a pioneering researcher in cognitive robotics, whose work bridges the gap between biological attention mechanisms and autonomous machine intelligence. His foundational research explores how robots can perceive, reason, and act through embodied simulation and attention-based control. Kasderidis introduced the influential framework of **Attentional Agents**, which models robot cognition as a process of managing multiple, often conflicting, sensory inputs through selective focus—a concept detailed in his highly cited 2004 paper (12 citations). His major contributions include developing hierarchical neural architectures inspired by human brain guidance for perception and action (2009, 14 citations), and advancing multi-target tracking techniques for mobile robots using laser range scanners (2008, 14 citations). With over 95 total citations across his ten most-cited works, Kasderidis has demonstrated how robots can learn sensorimotor maps through exploration and even imagine actions before executing them. His 2013 paper on inference through embodied simulation (19 citations) remains a cornerstone for researchers seeking to create cognitive machines that reason by mentally simulating interactions with their environment.

Research Focus

Key Achievements

6
H-Index
11
Papers
97
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Inference Through Embodied Simulation in Cognitive Robots
19 citations · 2013
📈 Most Prolific Year: 2008 (3 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Novocaptis (Greece), Foundation for Research and Technology Hellas, King's College London, King's College School, Hella (Germany)

Top Papers

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    Attention-based learning
    3 citations · 2005

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago