Demonstration of EDFA cognitive gain control via GMPLS for mixed modulation formats in heterogeneous optical networks. - Juliano Oliveira; Antonio Caballero 003; Eduardo Magalhães; Uiara Moura; Robert Borkowski; Giovanni Curiel; Alberto T. Hirata; Luis Henrique Hecker de Carvalho; Edson Porto da Silva; Darko Zibar; Jose Maranhao; Idelfonso Tafur Monroy; et al. (OFC/NFOEC, 2013)

SDN-enabled EDFA gain adjustment cognitive methodology for dynamic optical networks. - Uiara Moura; Miquel Garrich; Heitor Carvalho; Matheus Svolenski; Alexandre D. Andrade; Fabio Margarido; Amílcar C. César; Evandro Conforti; Juliano Oliveira (ECOC, 2015)

Estimating EDFA output power with an efficient numerical modeling framework. - Yue Fei; Andrea Fumagalli; Miquel Garrich; Benjamin Sarti; Uiara Moura; Neil Guerrero González; Juliano R. F. Oliveira (ICC, 2015)

Pioneering hardware modeling and software design for optical infrastructure in the Autonomous Network project. - Miquel Garrich; Anderson Bravalheri; Matheus Magalhaes; Heitor Carvalho; Juliano Assine; Henrique Rusa; Hugo Yamamura; Fabian van't Hooft; Uiara Moura; Joao Januario; Marcelo Ribeiro Nascimento; Leonardo Mariote; et al. (ONDM, 2016)

Local and global approaches for the adaptive control of a cascade of amplifiers. - Erick de A. Barboza; Carmelo J. A. Bastos Filho; Joaquim F. Martins-Filho; Marcionilo J. da Silva; Leonardo D. Coelho; Uiara C. de Moura; Juliano R. F. Oliveira (Photonic Netw. Commun., 2017)

Machine learning-based EDFA Gain Model Generalizable to Multiple Physical Devices. - Francesco Da Ros; Uiara Celine de Moura; Metodi P. Yankov (ECOC, 2020)

Power Evolution Prediction and Optimization in a Multi-span System Based on Component-wise System Modeling. - Metodi P. Yankov; Uiara Celine de Moura; Francesco Da Ros (ECOC, 2020)

Load Aware Raman Gain Profile Prediction in Dynamic Multi-Band Optical Networks. - A. Margareth Rosa Brusin; Uiara C. de Moura; Andrea D'Amico; Vittorio Curri; Darko Zibar; Andrea Carena (OFC, 2020)

Experimental Demonstration of Arbitrary Raman Gain-Profile Designs using Machine Learning. - Uiara C. de Moura; Francesco Da Ros; A. Margareth Rosa Brusin; Andrea Carena; Darko Zibar (OFC, 2020)

Advancing Classical and Quantum Communication Systems with Machine Learning. - Darko Zibar; Uiara C. de Moura; Hou-Man Chin; A. Margareth Rosa Brusin; Nitin Jain; Francesco Da Ros; Sebastian Kleis; Christian G. Schaeffer; Tobias Gehring; Ulrik L. Andersen; Andrea Carena (OFC, 2020)

Generalization Properties of Machine Learning-based Raman Models. - Uiara C. de Moura; Darko Zibar; A. Margareth Rosa Brusin; Andrea Carena; Francesco Da Ros (OFC, 2021)

Optimization of a Hybrid EDFA-Raman C+L Band Amplifier through Neural-Network Models. - Francesco Da Ros; Uiara C. de Moura; Ruben S. Luis; Georg Rademacher; Benjamin J. Puttnam; Ann Margareth Rosa Brusin; Andrea Carena; Yoshinari Awaji; Hideaki Furukawa; Darko Zibar (OFC, 2021)

Comparison of Models for Training Optical Matrix Multipliers in Neuromorphic PICs. - Ali Cem; Siqi Yan; Uiara Celine de Moura; Yunhong Ding; Darko Zibar; Francesco Da Ros (OFC, 2022)

Machine learning applied to inverse systems design. - Uiara C. de Moura; Francesco Da Ros; Darko Zibar; Ann Margareth Rosa Brusin; Andrea Carena (ONDM, 2022)

Online versus Offline Optimization Methods for Raman Amplifier Optimization. - Uiara C. de Moura; TiagoC Pinto; Ann Margareth Rosa Brusin; Andrea Carena; Antonio Napoli; Darko Zibar; Francesco Da Ros (OECC/PSC, 2022)

Flexible Raman Amplifier Optimization Based on Machine Learning-aided Physical Stimulated Raman Scattering Model. - Metodi Plamenov Yankov; Francesco Da Ros; Uiara Celine de Moura; Andrea Carena; Darko Zibar (CoRR, 2022)