Francesca Stramandinoli
University of Plymouth, Italian Institute of Technology, Hartford Financial Services (United States)
Papers
13
Total Citations
247
H-Index
7
About
Francesca Stramandinoli is a cognitive robotics researcher whose work sits at the intersection of language acquisition, embodied cognition, and human-robot interaction. She has made significant contributions to one of robotics' most challenging frontiers: enabling robots to understand and ground abstract concepts — words like "use" and "make" — in sensorimotor experience, moving beyond concrete object recognition toward genuinely human-like language comprehension. Her most cited work, "The grounding of higher order concepts in action and language" (2012, 64 citations), pioneered neural network approaches to symbol grounding in humanoid robots, a thread she developed across numerous subsequent publications. Her 2016 contributions span language abstraction modeling, benchmarking human-robot interaction metrics (61 citations), and embodied statistical language models — collectively establishing her as a leading voice in cognitive robotics methodology. Her 2018 review of abstract concept learning in embodied agents (37 citations) synthesized the field's computational approaches, offering an invaluable resource for researchers. More recently, Stramandinoli has extended her work into human-robot collaboration, developing deep learning architectures for reactive robot planning. With over 230 cumulative citations, her research has meaningfully advanced the scientific community's understanding of how robots can develop richer, more flexible cognitive and communicative capabilities.
Research Focus
Key Achievements
Top Papers
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- 3A review of abstract concept learning in embodied agents and robots37 citations · 2018
- 4Making sense of words: a robotic model for language abstraction25 citations · 2016
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