Jasmin Kajopoulos

Ludwig-Maximilians-Universität München

Papers

3

Total Citations

148

H-Index

3

About

Jasmin Kajopoulos is a pioneering researcher at the intersection of cognitive science, human-robot interaction, and clinical therapy. Her work fundamentally explores how humans perceive and attribute intentionality to artificial agents, with a specific focus on the perceptual mechanisms that distinguish agents from non-agents. Kajopoulos’s landmark study, "Humans are Well Tuned to Detecting Agents Among Non-agents" (59 citations), demonstrates that humans possess an innate sensitivity to behavioral cues of intentional systems, a finding with profound implications for robotics and AI design. She has made transformative contributions to autism therapy through her highly cited work "Robot-Assisted Training of Joint Attention Skills in Children Diagnosed with Autism" (51 citations), which systematically examined the cognitive mechanisms affected by robot-assisted interventions—a field previously lacking rigorous empirical study. Her research on "Autistic traits and sensitivity to human-like features of robot behavior" (38 citations) further reveals how individual differences in autistic traits modulate perception of robot social cues, using a novel non-verbal Turing test paradigm. Kajopoulos’s work bridges fundamental cognitive science and applied clinical robotics, establishing her as a leading voice in understanding how humans—both neurotypical and neurodivergent—engage with artificial social agents.

Research Focus

Key Achievements

3
H-Index
3
Papers
148
Total Citations
49
Avg Citations/Paper
🏆 Most Cited Paper
Humans are Well Tuned to Detecting Agents Among Non-agents: Examining the Sensitivity of Human Perception to Behavioral Characteristics of Intentional Systems
59 citations · 2015
📈 Most Prolific Year: 2015 (3 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Ludwig-Maximilians-Universität München

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago