Mauro Dalla Mura

情報・人工知能研究

Mauro Dalla Mura

特任准教授

Remote sensingImage and signal processingComputational imaging

略歴

Mauro Dalla Mura received the B.Sc. and M.Sc. degrees in Telecommunication Engineering from the University of Trento, Italy in 2005 and 2007, respectively.
He obtained in 2011 a joint Ph.D. degree in Information and Communication Technologies from the University of Trento and in Electrical and Computer Engineering from the University of Iceland, Iceland.
In 2011 he was a Research fellow at Fondazione Bruno Kessler, Trento, Italy, conducting research on computer vision.
He is currently an Associate Professor at Grenoble Institute of Technology (Grenoble INP), France since 2012. He is conducting his research at the Grenoble Images Speech Signals and Automatics Laboratory (GIPSA-Lab). Dr. Dalla Mura has been appointed "Specially Appointed Associate Professor" at the School of Computing, group of Prof. K. Shinoda, Tokyo Institute of Technology, Japan for the period 2019-2022. His main research activities are in the fields of remote sensing, image and signal processing and computational imaging.
Dr. Dalla Mura was the recipient of the IEEE GRSS Second Prize in the Student Paper Competition of the 2011 IEEE IGARSS 2011 and co-recipient of the Best Paper Award of the International Journal of Image and Data Fusion for the year 2012-2013 and the Symposium Paper Award for IEEE IGARSS 2014.
Dr. Dalla Mura is the President of the IEEE GRSS French Chapter since 2016 (he previously served as Secretary 2013-2016). In 2017 the IEEE GRSS French Chapter was the recipient of the IEEE GRSS Chapter Award and the ``Chapter of the year 2017'' from the IEEE French Section. He is on the Editorial Board of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS) since 2016.

WRHIへの期待

Remote sensing has a fundamental role in Earth observation for many scientific, societal and economical tasks. However, remote sensing presents several challenges in extracting information from the acquired data due to their heterogeneity and huge size.
Conducting research at WRHI, Tokyo Institute of Technology, offers a great opportunity for joining forces and expertise from different disciplinary fields as data science, image and signal processing, artificial intelligence and computational imaging. This will give the possibility to develop effective solutions for addressing the analysis of remote sensing data for tasks such as precision agriculture.

2011

PhD in Information and Communication Technologies from the University of Trento and in Electrical and Computer Engineering from the University of Iceland, Iceland

2011-2012

Research fellow at Technology of Vision, Fondazione Bruno Kessler, Trento, Italy

2012-

Associate Professor at Grenoble Institute of Technology and Grenoble Images Speech Signals and Automatics Laboratory (GIPSA-Lab), Grenoble, France

2019-

Specially Appointed Associate Professor, School of Computing, Tokyo Institute of Technology

2011

IEEE GRSS Second Prize in the Student Paper Competition at IEEE IGARSS 2011

2014

Best Paper Award of the International Journal of Image and Data Fusion

2014

Symposium Paper Award at IEEE IGARSS 2014

2010

M. Dalla Mura, J. Atli Benediktsson, B. Waske, and L. Bruzzone, “Morphological attribute profiles for the analysis of very high resolution images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 10, pp. 3747–3762, 2010.

2015

M. Dalla Mura, S. Prasad, F. Pacifici, P. Gamba, J. Chanussot, and J. Benediktsson, “Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing,” Proceedings of the IEEE, vol. 103, no. 9, pp. 1585–1601, Sep. 2015.

2017

G. Cavallaro, N. Falco, M. Dalla Mura, and J. A. Benediktsson, “Automatic Attribute Profiles,” IEEE Transactions on Image Processing, vol. 26, no. 4, pp. 1859–1872, 2017.

2018

M. Malfante, M. Dalla Mura, J.-P. Métaxian, J. I. Mars, O. Macedo, and A. Inza, “Machine learning for volcano-seismic signals: Challenges and perspectives,” IEEE Signal Processing Magazine, vol. 35, no. 2, pp. 20–30, 2018.