Foto del docente

Roberto Meattini

Adjunct professor

Department of Industrial Engineering

Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi"

Research fellow

Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi"

Curriculum vitae

SHORT CURRICULUM VITAE

  • Roberto Meattini, in 2014, got the Master's Degree in Automation Engineering at the University of Bologna, with final grade of 110/110 cum laude.
  • In 2018, he got the PhD in Biomedical, Electrical and Systems Engineering (XXX Cycle), within the "Automatic Control and Operational Research" curriculum, at the Department of Electrical, Electronic and Information Engineering "Gugliemo Marconi" (DEI) of the University of Bologna, under the supervision of Prof. Claudio Melchiorri.
  • From 2017 to 2018, he was Visiting Scientist at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR), Germany.
  • Since 2018, he is Research Fellow (post-doc) at the Department of Electrical, Electronic and Information Engineering "Gugliemo Marconi" (DEI) of the University of Bologna.
  • Since 2019, he is Adjunct Professor of the academic course "Engineering and Technologies of Control Systems", for the MSc in Mechanical Engineering of the University of Bologna.
  • Since 2019, he participates to the project REMODEL (Robotic technologies for the manipulation of complex deformable linear objects) coordinated by Prof. Gianluca Palli, funded by the European Commission under the H2020 program.
  • Since 2022, he is Adjunct Professor of the academic course "Foundations of Industrial Robotics", for the BSc in Automation Engineering of the University of Bologna.
  • He received a best conference paper award (IEEE ROBIO 2017.)
  • His research interests are mainly related to: robotic manipulation and telemanipulation; cognitive and physical human-robot interaction (HRI); electromyography (EMG) interfaces for the control of robotic devices; multimodal control of wearable and grounded robots; assistive and prosthetic robotics; wearable sensors and machine learning for human intent estimation for robotic applications.

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