Editor - Filippo Cavallo | BioRobotics Institute of Scuola Super | 19906

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Filippo Cavallo

Filippo Cavallo
Filippo Cavallo
Assistant professor
BioRobotics Institute of Scuola Superiore Sant’Anna


Filippo Cavallo, MScEE, Phd in Bioengineering, is Assistant Professor at the BioRobotics Institute of Scuola Superiore Sant’Anna, (Pisa, Italy), focusing on cloud and social robotics, ambient assisted living, wireless and wearable sensor systems, biomedical processing, acceptability and ICT and AAL roadmapping. He participated in various National and European projects and currently is project manager of Robot-Era, AALIANCE2 and Parkinson Project. He was visiting researcher at the the EndoCAS Center of Excellence, Pisa, Italy working in Computer Assisted Surgery (2005- 2007); at the Takanishi Lab, Waseda University, Tokyo, Japan working on wireless sensor network (2007); at Tecnalia Recerch Center, Basque Country, Spain working on wearable sensor system for AAL. He was granted from the International Symposium of Robotics Research Committee as Fellowship Winner for best PhD thesis in Robotics (2007); from the Regional POR FSE 2007-2013 for a 3-years Research position at The BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera, Italy (2010-2013); from the ACCESS-IT 2009 for the Good Practise Label in Alzheimer Project (2009); from the Well-Tech Award for Quality of Life with the Robot-Era Project (2014); from the SMAU Award for Quality of Life with the Robot-Era Project (2014). He is author of various papers on conferences and ISI journals.

Research Interest

Service and Assistive Robotics for “ageing well” applications, including integration of robotic systems in smart environments, navigation and localization techniques, and advanced natural human robot interfaces. • Wireless sensor networks for Smart Environments and Ambient Assisted Living applications, including development of environmental and wearable sensors with low-power design, Ambient Intelligent algorithms, networking strategies, and localization. • Wearable sensor network for musculoskeletal modeling of human body and their application to biomechanics, gesture analysis and human motion measurement.



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