In order to honor Professor Fernando Nicolau, founding member and co-responsible for the creation of the Portuguese Association for Classification and Data Analysis (CLAD), recognizing his visionary initiative and unusual dedication, the FERNANDO NICOLAU AWARD has been established, in accordance with the decision of the Board of CLAD and subsequent communication of this initiative at the General Assembly of CLAD on March 10, 2021.
The FERNANDO NICOLAU AWARD will be held every two years, and aims to disseminate and reward works in Data Science and Classification and Analysis published internationally by CLAD members, stimulating publication in CLAD’s scientific areas.
The jury of the FERNANDO NICOLAU AWARD 2023 is composed by Professor Helena Bacelar-Nicolau (University of Lisbon, Honorary President), Professor Gilbert Saporta (Professor Emeritus, CNAM, Paris), Professor Paulo Gomes (Information Management School, Universidade Nova de Lisboa) and Professor Mário Figueiredo (Institute of Telecommunications, Instituto Superior Técnico, University of Lisbon).
See here the regulation: Fernando Nicolau Award 2025.
Application deadline: 16 January 2025.
Register here using the Registration Form: HERE.
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PAST AWARD: 2023
Among the papers submitted for the 2021 edition, two were identified as meeting the conditions of the respective Edital. The FERNANDO NICOLAU AWARD 2023 was given to Maria Eduarda Silva, for the work:
Silva, V. F.; Silva, M. E.; Ribeiro, P.; Silva, F. Novel features for time series analysis: a complex networks approach. Data Mining and Knowledge Discovery, 2022, 36, 1062-1101.
An Honourable Mention was also given for the work: ‘No Free Lunch in imbalanced learning’ by Nuno Moniz and Hugo Monteiro.
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PAST AWARD: 2021
Among the papers submitted for the 2021 edition, two were identified as meeting the conditions of the respective Edital. The FERNANDO NICOLAU AWARD 2021 was given to M. Rosário Oliveira, for the work:
Theoretical foundations of forward feature selection methods based on mutual information, Macedo, F., Oliveira, M. R., Pacheco, A., & Valadas, R., Neurocomputing, 325, 67-89, (2019).
