About me

I am Computer Engineer, Assistant Professor at the TeCiP Institute of Scuola Superiore Sant’Anna (SSSA) in Pisa, Italy, researching and developing interfaces and systems for humans in AR/VR and HRI employing approaches in computer vision and machine learning. This started from the initial interest in haptics and training for humans. More recently I am interested in several aspects of Deep Learning for Computer Vision aimed at HMI. I am also a software developer versed in C++ and Python.

I am leading the group Sensing Modeling and Learning for Humans at PERCRO laboratory.

Short Bio

Assistant Professor at SSSA (2007-)
Visiting researcher at Stanford University (2005-2006)
Scuola Superiore Sant’Anna (PhD 2003-2006)
Visiting scholar at UCL (2003)
University of Pisa (MS, Computer Engineering 1997-2002)

Research Topics

While the research listing is being updated please find below the visual listing of publications (link)

Interaction in Virtual Environments – 2003-
Research in different aspect of the interaction in Virtual Environments spanning from embodiment, haptic interaction, interaction modalities. This is also related to the Personal timeline on VR. One of the interests is the mataphor of Information Landscape in immersive (dimea08) and desktop contexts.
Haptic Interaction Techniques and Haptic Rendering – 2006-
Investigation of haptic rendering techniques in different scenarios.
  • 6DOF haptic rendering based on volume data (haptics08).
  • Co-Located haptic rendering for USG training based on implicit surfaces (embc15)
  • Exoskeleton based virtual embodiment with avatars (eh2014_exos)
Full spectrum research in the use of VE for training sport with specific focus on Rowing. The research spanned from the technical design and construction of the environment, to human motion data analysis, training protocol design up to assessment experiments in different skills of the rowing task such as energy, team coordination and technique.
When the computing problem is not explicitly parallel, but it instead organised in multiple concurrent flows there is the need of optimizing the resource usage. This  The SOMA framework proposes an approach based on static code analysis and profiling for producing new efficient scheduling. The CoCo system, instead, proposed a concurrent data-flow for Mixed Reality applications. Finally research is undergoing in the area of code generation for multicore probabilistic graphical model inference.
Research in the area of wearable inertial sensor fusion and wearable EMG for the analysis of actions in working environments, also called Occupational Biomechanics. Experimental results are reported for the reconstruction with multiple sensors based on Unscented Kalman Filtering toward the use of Probabilistic Graphical Models. Working load experiments have been performed comparing the system with manual annotations.
Investigation of haptic rendering solution and embedding for a novel type of roboti
c rehabilitation device that generates forces using the wheels. The resulting systems allows to perform several types of rehabilitation devices. Additional research in the area of sensor-fusion


I am participating to research projects at European, National and Industrial level as Principal Investigator

  • RAMCIP H2020 (PI) – robotics
  • INAIL BRIC 24 (Coordinator) – harbour worker biomechanics and behavior using wearable sensors and artificial intelligence

Recent Past projects

  • REMEDI FP7 – tele-presence and haptics for medical domain
  • PELARS FP7 – multimodal learning analytics

Options for tentative Students


I am teaching mainly PhD level courses in the domains of Computer Vision and Virtual Environments with some additional lectures on Machine Learning and Tools.

Sensing, Modeling and Learning for Humans Group

  • Lorenzo Peppoloni (Postdoc) – Human Analysis
  • Giulia Bassani (Postdoc) – Wearable
  • Lorenzo Landolfi (PhD) – Vision and Deep Learning
  • Giacomo Dabisias (PhD) – Vision and Deep Learning
  • Filippo Brizzi (c/o PhD) – AR/VR
  • Michele Tonutti  (post grad) – Deep Learning
  • Alessandro Cattaneo (master thesis) – Deep Learning
We recently started a Deep Cafè group meetings.

Graduated PhDs

  • Giulia Bassani – SSSA
  • Lorenzo Peppoloni – SSSA
  • Alessandro Filippeschi – SSSA
  • Alessandro di Fava – PAL Robotics
  • Leonard Johard – Innopolis
  • Vittorio Lippi – Freiburg University