L'inizio delle lezioni del corso "DRONI PER IL RILIEVO GEOREFERENZIATO URBANO E TERRITORIALE E ANALISI DI DATI SPAZIALI" è posticipato a mercoledì 27 settembre.
Legenda
Andrea is Associate Professor of Geomatics at the Department of Civil and Environmental Engineering of the University of Florence. He received his MSc Degree in Computer Engineering and his PhD degree in Automatic Control and Operational Research from the University of Padua. He held a post-doc position at the Interdepartmental Research Center of Geomatics of the University of Padua from 2012 to 2019. He teaches Geomatics, Topography and Cartography, Photogrammetry, Least Squares Adjustment, Positioning and Navigation courses for MSc and PhD students.
He is committed in national and international scientific committees (secretary of ISPRS WG I/7 Mobile Mapping Technology 2016-2021, chair of IAG WG Vision Aided Positioning and Navigation 2020-2024) and research groups related to geomatics. He was visiting researcher at the Department of Geomatics of the University of Calgary (Canada), Mobile Multi-Sensor System (MMSS) Research Group, in 2018, and at the Digital Photogrammetry Research Group (DPRG) of the Purdue University (West Lafayette, US), in 2017.
He has been in the scientific committee of several international scientific conferences, and co-organizer of the 12th International Conference on Mobile Mapping Technology 2021. He is author of 80+ articles in international scientific journals, conference proceedings and book chapters. He is the recipient of best paper and best poster awards in International Scientific conferences (ISPRS TCII symposium 2018, FIG working week 2019) and FIG article of the month July and August 2019.
His research interests range from Geomatics, Mobile Mapping, Positioning and Navigation, Machine Learning to Computer Vision, Smart Camera Networks, modeling and control of Adaptive Optics systems. His research mainly focused on sensor integration and information fusion, positioning, photogrammetry, LiDAR data processing, visual and LiDAR odometry, statistical and mathematical modelling, machine and deep learning.
