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Davide Boscaini was born in Verona (Italy) in 1988. He received a B.S. degree in Applied Mathematics in 2010 and a M.S. degree in Mathematics in 2012, both from the University of Verona (Italy). His master thesis on "Spectral Methods for Shape Analysis" was developed during an intership at the Vision, Image, Processing and Sound Lab on topics related with the analysis of 3D deformable objects. The desire to deepen his knowledge in this topic led Davide to start a Ph.D. at the University of Lugano (Switzerland) under the supervision of prof. Michael M. Bronstein. During the Ph.D. his research focussed on merging spectral approaches and deep learning techniques to develop novel algorithms for 3D Shape Analysis. Davide's efforts contributed to the birth of a new research field, called Geometric Deep Learning, aiming at extending deep learning techniques to geometric domains such as 3D shapes and graphs. He received his Ph.D. degree in Computer Science in 2017 with a dissertation on "Geometric Deep Learning for Shape Analysis". He is currently a researcher at the Technologies of Vision research unit of the Fondazione Bruno Kessler in Trento (Italy).
Boscaini, Davide; Eynard, Davide; Bronstein, Michael M.,2014
Boscaini, Davide; Castellani, Umberto,Local signature quantization by sparse coding,Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval (3DOR '13),2013, pp. 9-16, (Sixth Eurographics Workshop on 3D Object Retrieval (3DOR '13),Girona, Spain,May 11 - 11, 2013)