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Alessandro Giusti
Also published under:A. Giusti
Affiliation
USI-SUPSI, Dalle Molle Institute for Artificial Intelligence (IDSIA), Lugano, Switzerland
Topic
Convolutional Neural Network,Pose Estimation,Neural Network,Training Set,Unmanned Aerial Vehicles,Human Pose Estimation,Inertial Measurement Unit,Self-supervised Learning,Deep Neural Network,Ground Robots,Human-robot Interaction,Mean Absolute Error,Pretext Task,Relative Pose,Camera Images,Commercial Off-the-shelf,Conveyor Belt,Convolutional Layers,Eristalis,Fine-tuned Model,Ground Truth Labels,On-chip Memory,Onboard Computer,Power Consumption,Real-world Data,Training Data,Visual Feedback,3D Space,Autoencoder,Autonomic System,Autonomous Navigation,Backward Pass,Barycenter,Body Frame,Body Tracking,Control Performance,Depth Map,Domain Shift,Fine-tuning Process,Forward Pass,Fully Convolutional Network,Gaze Cues,Gestures,Grayscale Images,Hand Movements,Horizontal Axis,Human Intention,Image Area,Image Coordinates,Image Plane,
Biography
Alessandro Giusti received the Ph.D. degree in computer science from the Politecnico di Milano, Milan, Italy, in 2009.
He is currently a Professor of Artificial Intelligence for Autonomous Robotics with the Dalle Molle Institute for Artificial Intelligence (IDSIA), USI-SUPSI, Lugano, Switzerland. His research focuses on human–robot interaction and self-supervised deep learning for perception tasks in aerial, ground and industrial robotics.
Prof. Giusti work has resulted in 100+ publications in international conferences and journals and has been awarded several times, including the 2020 IEEE Communications Society Charles Kao Award, the Best Demo and Best Video Awards at HRI 2019, the shortlist for the AAAI 2016 Video Competition, the $1^{st}$ place in three international competitions on biomedical image analysis, and four additional best paper awards.
He is currently a Professor of Artificial Intelligence for Autonomous Robotics with the Dalle Molle Institute for Artificial Intelligence (IDSIA), USI-SUPSI, Lugano, Switzerland. His research focuses on human–robot interaction and self-supervised deep learning for perception tasks in aerial, ground and industrial robotics.
Prof. Giusti work has resulted in 100+ publications in international conferences and journals and has been awarded several times, including the 2020 IEEE Communications Society Charles Kao Award, the Best Demo and Best Video Awards at HRI 2019, the shortlist for the AAAI 2016 Video Competition, the $1^{st}$ place in three international competitions on biomedical image analysis, and four additional best paper awards.