Mário Antunes is currently an Associate Professor at the University of Aveiro. He received his Ph.D. degree in Computer Science from the MAPi joint doctoral program in 2018 and was a finalist in three internationally renowned competitions in 2019, including the ERCIM Cor Baayen Young Investigator Award, the Altice International Innovation Award, and the Best Technological Innovation Doctoral Dissertation Award. His current research interests focus on the modulation and characterization of shallow and deep learning models, as well as advanced time series analysis, modulation, and prediction. He is also actively working on the efficient exploitation of Large Language Models and Federated Learning in heterogeneous environments, alongside specific optimization challenges such as blind optimization initialization, knee detection, and empty space search. To date, Mário has published more than 100 papers and actively maintains seven Python libraries that support the computational frameworks developed in his research.
Mário Antunes is currently an Associate Professor at the University of Aveiro. He received his Ph.D. degree in Computer Science from the MAPi joint doctoral program in 2018 and was a finalist in three internationally renowned competitions in 2019, including the ERCIM Cor Baayen Young Investigator Award, the Altice International Innovation Award, and the Best Technological Innovation Doctoral Dissertation Award. His current research interests focus on the modulation and characterization of shallow and deep learning models, as well as advanced time series analysis, modulation, and prediction. He is also actively working on the efficient exploitation of Large Language Models and Federated Learning in heterogeneous environments, alongside specific optimization challenges such as blind optimization initialization, knee detection, and empty space search. To date, Mário has published more than 100 papers and actively maintains seven Python libraries that support the computational frameworks developed in his research.