Guilherme Aldeia
Guilherme Aldeia is a Ph.D. student in the field of Computer Science at the Universidade Federal do ABC. He graduated in Computer Science and Neuroscience, obtained a Master’s degree in Computer Science, and is interested in symbolic regression, interpretability, heuristics, and computational models. His past works focused on interpretability in symbolic regression, the usage of fMRI data in machine learning, and computational neural models. In 2017, he decided to pursue an academic career, aiming to become a researcher and professor.
Recent Papers
Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models
Machine Learning for Healthcare
Recent Posts
Relaxing the definition of equivalent mathematical expressions to get simpler and more interpretable models