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Francesco Guidi

Professore a contratto

Dipartimento di Ingegneria Industriale

Curriculum vitae

Dr. Francesco Guidi received the M.S. degree (summa cum laude) in electronics and telecommunications engineering from the University of Bologna, Italy, in 2009, and the joint Ph.D. degree in Information Engineering from the Ecole Polytechnique, Paris, France and from the University of Bologna in 2013.

He is currently a Researcher at the National Research Council of Italy (CNR), Institute of Electronics, Computer and Telecommunication Engineering (IEIIT), and an Adjunct Professor at the University of Bologna.

In 2018, he was a Visiting Scholar at Stony Brook University, New York, USA, for 8 months.

From 2015 to 2017, he held a Research Position with an individual European Marie-Curie Fellowship, funded by the European Commission, at the French Alternatives and Atomic Energy Commission (CEA), LETI, Grenoble, France.

From 2013 to 2015, he was a Research Fellow with the University of Bologna.

In 2014 he was a consultant for Datalogic IpTech, Bologna, Italy.

In 2010 he was awarded with the "Vinci" fellowship from the "Université Franco-Italienne". Then, he was the recipient of the "CNIT Ideas Award" in 2018, and co-recipient of the Best Student Paper Award at the International Conference on UltrawideBand (Paris, France) in 2014, and of the Best Paper Award at the International Conference on Autonomous Systems (Montreal, Canada) in 2021. In 2022 and 2023 he was awarded as Exemplary Reviewer for the IEEE Communications Letters.

He has been a Chair for a number of Workshops and Special Sessions presented at ICC'23 and ICC'24, ICASSP'23 and ICASSP'24, VTC-Spring'22, EUSIPCO'22, VTC-Fall'22 and EUCNC'21.

He is a Reviewer for different journals and projects (e.g., for the Swedish Research Council), and he is an Associate Editor for the IEEE Wireless Communications Letters, a Topic Editor for Sensors, and one of the Guest Editors of the Eurasip Journal on Advances in Signal Processing, Special Issue on  "Signal Processing and Machine Learning in Autonomous Systems".

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