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Alcides Fonseca is an Assistant Professor at the University of Lisbon, where he conducts research on the Gloss group at the LASIGE research unit. He holds a Ph.D. in Parallel Programming from the University of Coimbra where he was a member of CISUC and worked on the AEminium project. His main research interests are automatic programming, parallel programming, machine learning and evolutionary computation. He has developed automatic parallelizing compilers for Java, programming languages and machine-learning-powered high-performance runtime libraries for efficiently execution of programs on CPUs and GPUs.
- Fonseca, Alcides, and Bruno Cabral. "Controlling the granularity of automatic parallel programs." Journal of Computational Science 17 (2016): 620-629.
- Fonseca, Alcides, et al. "Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime." International Journal of Parallel Programming 44.6 (2016): 1337-1358.
- Fonseca, Alcides, and Bruno Cabral. "Prototyping a GPGPU Neural Network for Deep-Learning Big Data Analysis." Big Data Research (2017).
- Stork, Sven, et al. "Aeminium: A permission-based concurrent-by-default programming language approach." ACM Transactions on Programming Languages and Systems (TOPLAS) 36.1 (2014): 2.
- Fonseca, Alcides, and Bruno Cabral. "Æminiumgpu: an intelligent framework for gpu programming." Facing the Multicore-Challenge III. Springer Berlin Heidelberg, 2013. 96-107.