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Staff

Diego Valsesia

Associate Professor (L. 240)
Department of Electronics and Telecommunications (DET)

Profile

Keywords

Artificial intelligence
Computer vision and pattern recognition
Deep learning
Digital image processing
Graph neural networks
Remote sensing
Signal denoising
Super-resolution

Biography

He is currently an Associate Professor with the Department of Electronics and Telecommunications (DET). His main research interests include processing of remote sensing images, and deep learning for inverse problems in imaging. He is a Senior Area Editor for the IEEE Transactions on Image Processing, for which he received the 2023 Outstanding Editorial Board Member Award. He is a member of the EURASIP Technical Area Committee for Signal and Data Analytics for Machine Learning and a member of the ELLIS society. He was the recipient of the IEEE ICIP 2019 Best Paper Award, the IEEE Multimedia 2019 Best Paper Award.

Scientific branch

IINF-03/A - Telecommunications
(Area 0009 - Industrial and information engineering)

Skills

ERC sectors

PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
PE7_7 - Signal processing

SDG

Goal 11: Sustainable cities and communities

Awards and Honors

  • Top 10% Paper Award at 2013 IEEE International Workshop on Multimedia Signal Processing conferred by 2013 IEEE lnternational Workshop on Multimedia Signal Processing (MMSP) organizing committee, Italy (2013)
  • Best Demo Award IEEE SPS Italy Chapter Summer School on Signal Processing conferred by IEEE SPS Italy Chapter, Italy (2013)
  • First place Proba-V Superresolution challenge conferred by European Space Agency, Italy (2019)
  • Best Paper Award IEEE ICIP 2019 conferred by IEEE International Conference on Image Processing (ICIP) 2019, Italy (2019)
  • Best Paper Award conferred by IEEE Multimedia, Italy (2020)
  • Outstanding Editorial Board Member Award conferred by IEEE Transactions on Image Processing, United States (2023)
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Editorial boards

  • IEEE TRANSACTIONS ON IMAGE PROCESSING (2021-), Associate Editor of magazine or editorial series

Conferences

  • EUSIPCO 2025, Program committee

Other titles

  • Pytorch-)

Research networks

  • ELLIS Society (2020-). Partecipazione

Teaching

Collegi of the degree programmes

Teachings

PhD

MostraNascondi A.A. passati

Master of Science

MostraNascondi A.A. passati

Bachelor of Science

MostraNascondi A.A. passati

Research

Research fields

Research projects

Projects funded by competitive calls

Supervised PhD students

  • Luca Dordoni. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (39th cycle, 2024-in progress)
    Research subject: The thesis aims at developing techniques for deep learning-based multi-modal image processing
    Big Data, Machine Learning, Neural Networks and Data Science
    Big Data, Machine Learning, Neural Networks and Data Science
  • Gabriele Inzerillo. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (39th cycle, 2024-in progress)
    Research subject: Bringing change detection on board satellites for low-latency damage assessment
    Big Data, Machine Learning, Neural Networks and Data Science
    Multimedia Signal Processing
    Big Data, Machine Learning, Neural Networks and Data Science
    Multimedia Signal Processing
  • Davide Piccinini. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (39th cycle, 2024-in progress)
    Research subject: My work focuses on remote sensing applications and deployment of deep learning techniques.
    Big Data, Machine Learning, Neural Networks and Data Science
    Big Data, Machine Learning, Neural Networks and Data Science
  • Alessandro Scarciglia. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (39th cycle, 2024-in progress)
  • Ziyao Yi. Programme in Intelligenza Artificiale (39th cycle, 2023-in progress)
  • Luca Savant Aira. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (38th cycle, 2022-in progress)
    Thesis: Deep Learning for 3D World Representations
    Big Data, Machine Learning, Neural Networks and Data Science
    Multimedia Signal Processing
    Big Data, Machine Learning, Neural Networks and Data Science
    Multimedia Signal Processing
    Big Data, Machine Learning, Neural Networks and Data Science
    Multimedia Signal Processing
  • Emanuele Aiello. Programme in Intelligenza Artificiale (37th cycle, 2021-2025)
    Thesis: Generative and Multimodal Learning for Vision and Language
    Computer vision and image understanding
    3D vision and 3D reconstruction
    Self-supervised and semi-supervised learning
    Generative models and Generative Adversarial Networks
    Computer vision and image understanding
    3D vision and 3D reconstruction
    Self-supervised and semi-supervised learning
    Generative models and Generative Adversarial Networks
  • Antonio Montanaro. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (36th cycle, 2020-2024)
    Thesis: Exploring the latent geometry for representation learning
    Big Data, Machine Learning, Neural Networks and Data Science
    Geo-positioning, Navigation Systems and Remote sensing
    Big Data, Machine Learning, Neural Networks and Data Science
    Geo-positioning, Navigation Systems and Remote sensing
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Publications

Last years publications

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Knowledge Valorisation

Technology transfer