Lorenzo Carnevale
Papers
6
Total Citations
65
H-Index
4
About
Lorenzo Carnevale is a leading researcher at the intersection of socially assistive robotics, big data analytics, and healthcare technology. His work focuses on developing intelligent robotic systems—particularly humanoid robots like Pepper—to improve psychosocial and physical outcomes for persons with dementia and their informal caregivers. Carnevale’s major contributions include pioneering mixed-methods studies that compare robot-assisted interventions with tablet-based training, revealing how socially assistive robots can reduce caregiver burden and enhance patient engagement. His research on integrating big healthcare data into clinical workflows has also advanced the use of cloud-based systems for personalized rehabilitation, as seen in his work on robotic-assisted gait training. With over 65 citations across his most influential papers, Carnevale’s impact is evident in his ability to bridge robotics, distributed learning, and real-world clinical applications. Notably, his 2019 study on the effects of humanoid robots versus tablet training for dementia patients has garnered 35 citations, underscoring its significance. More recently, he has explored federated learning frameworks for robotics, pushing the boundaries of privacy-preserving, distributed AI in healthcare. Carnevale’s work is essential reading for anyone interested in how robotics and data science can transform patient care and support aging populations.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3How to enable clinical workflows to integrate big healthcare data9 citations · 2017
- 4
- 5
- 6