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'1000 Talent Contest' to professor Antonello Cutolo

The professor Antonello Cutolo, was awarded the '1000 Talent Contest, a prestigious academic recognition of the Chinese Government (managed together with the Chinese Academy of Sciences), reserved for foreign scientists who have distinguished themselves in the development of innovative technologies with important social implications.

The news on the UNINA website: http://www.unina.it/-/36447211-1000-talent-contest-al-professore-antonello-cutolo

5TH KIMURA BEST PAPER AWARD 2022 TO LAURA CELENTANO

We are pleased to announce that Prof. Laura Celentano has won the 5th Kimura Best Paper Award of Asian Journal of Control for the paper, co-authored by Professors M.V. Basin and M. Chadli, titled

L. Celentano, M.V. Basin, and M. Chadli, "Robust tracking design for uncertain MIMO systems using proportional-integral controller of order v," Asian Journal of Control, vol. 23, no. 5, pp. 2042-2063, 2021.

Prof. Celentano, as the representative recipient of this prestigious scientific recognition, will use the amount of the prize to fund supporting and mentoring projects for the Federico II female students of STEM disciplines.

Below, you can find the awarded manuscript and the link of the announcement: Robust tracking design for uncertain MIMO systems using proportional-integral controller of order v.pdf

https://onlinelibrary.wiley.com/page/journal/19346093/homepage/news.html

PICUSLAB GROUP TEAM RANK FIRST IN THE 2022 BIOASQ CHALLENGE

The team formed by Marco Postiglione (XXXVI PhD ICTH cycle), Giancarlo Sperlì (RTD-B Researcher) and Vincenzo Moscato (Associate Professor), members of the PicusLab group of the Department of Electrical Engineering and Information Technologies (DIETI), ranked first in the BioASQ 2022 challenge "DisTEMIST: Disease Text Mining Shared Task"

BioASQ organizes, on an annual basis, challenges on biomedical semantic indexing and question answering (QA). Challenges include tasks relevant to hierarchical text classification, machine learning, information retrieval, QA from structured text and data, multi-document summarization and many other areas.
In particular, the DisTEMIST challenge concerned the creation of a Natural Language Processing (NLP) system capable of indexing the content concerning diseases in biomedical texts in Spanish.
For further information:
BioASQ website: http://www.bioasq.org 
DisTEMIST challenge site: https://temu.bsc.es/distemist/ 
Challenge leaderboard: http://participants-area.bioasq.org/results/DisTEMIST/ 

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