Awards

The paper titled "An Emotional Recommender System for Music", whose authors are Vincenzo Moscato, Antonio Picariello and Giancarlo Sperlì, won the runner up award for best paper in IEEE Intelligent Systems for 2021.

Read more: Picuslab professors win runner up award for best paper for IEEE Intelligent Systems

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

ANVUR has published the list of 180 Departments eligible for funding for Departments of Excellence https://www.anvur.it/news/pubblicato-lelenco-dei-180-dipartimenti-di-eccellenza-2023-2027/, and our Department is, for the second time, among the selected Departments.

Read more: The DIETI Department selected as a department of excellence for the five-year period 2023-2027

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/