Supervision

MSc theses

Ana Sousa. Classifying Alzheimer’s Disease through Federated Learning and 3D Brain MRIs. Co-advised with António Sousa, Beatriz Cepa and Alícia Oliveira. University of Minho.
Ricardo Araújo. Neuroimaging analysis pipeline leveraging open-source frameworks in distributed environments. Co-advised with António Sousa and Beatriz Cepa. University of Minho.
Alexandre Fernandes. Energy Monitoring System for Large-Scale Infrastructures. Co-advised with Ricardo Macedo and António Sousa, University of Minho.
Carlos Machado. An NVMe-oriented I/O scheduler for reducing energy consumption. Co-advised with João Paulo and Ricardo Macedo, University of Minho.
Miguel Braga. *GPU Energy Control for LLMs. Co-advised with Ricardo Macedo and António Sousa, University of Minho.
Gonçalo Sousa. Fault-Tolerant storage solutions for AI training in HPC. Co-advised with João Paulo, University of Minho.
André Lucena. Storage Optimizations for large-scale AI training in HPC. Co-advised with João Paulo, University of Minho.

Alícia Oliveira. Correction of Motion Artifacts using Deep Learning in High-Performance Computing. Co-advised with António Sousa and Beatriz Cepa. University of Minho. Finished: 20 values
Diana Rodrigues. GPU energy control for Deep Learning systems. Co-advised with Ricardo Macedo and António Sousa, University of Minho. Finished: 19 values
Mariana Amorim. Energy control system for disaggregated storage resources. Co-advised with João Paulo and Ricardo Macedo, University of Minho. Finished: 18 values
José Fernandes. Comprehensive study of the energy impact of key-value stores. Co-advised with Ricardo Macedo and António Sousa, University of Minho. Finished: 19 values
Sara Pereira. Energy Control System for Large-Scale Infrastructures. Co-advised with Ricardo Macedo and Carlos Baquero, University of Porto. Finished: 18 values
Francisco Neves. Heterogeneous Storage Solution for Deep Learning Frameworks. Co-advised with João Paulo and Ricardo Macedo, University of Minho.

Maria Beatriz Moreira. “I/O Optimizations for Distributed Deep Learning Training”. Co-advised with João Paulo and Ricardo Macedo. University of Minho* Finished: 18 values
Luís Branco. Integration of Distributed Deep Learning in MCC application. Co-advised with António Sousa and Beatriz Cepa. University of Minho.

Beatriz Cepa. Deep Learning for Image Generation Using HPC. Co-advised with António Sousa. University of Minho. Finished: 18 values
Beatriz Soares. A Web and Machine Learning-based DICOM Image Tool. Co-advised with António Sousa. University of Minho. Finished: 20 values
João Alves.* Cloud-based Healthcare Application with Privacy-preserving Analytics. Co-advised with António Sousa. University of Minho. Finished: 19 values

Ana Cláudia Abreu. Distributed Deep Learning Approach for Epilepsy Detection on EEG signals. Co-advised with António Sousa. University of Minho. Finished: 17 values

Margarida Machado. Distributed Deep Learning For Sleep Apnea Detection on ECG signals. Co-advised with António Sousa. University of Minho. Finished: 18 values

Manuel Carvalho, Nuno Matos. Pipeline for the analysis of time series data based in AI models using distributed systems. Co-advised with Fábio Coelho (under the ATE project), University of Minho.

Diana Rodrigues, José Fernandes and Mariana Amorim. Monitoring Energy Consumption with Fine-Granularity in Data-centric Applications. Co-advised with António Sousa and Ricardo Macedo, University of Minho