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

Application of Artificial Neural Networks and Functional Brain Connectivity to Inform Pediatric Headache

Guilherme Aldeia, Clara Moon, Julie Shulman, Navil Sethna, Allison Smith, Alyssa Lebel, William La Cava, Scott Holmes (2025)

The Journal of Pain

jpain.org  |  pdf

Call for Action: towards the next generation of symbolic regression benchmark

Guilherme S. Imai Aldeia, Hengzhe Zhang, Geoffrey Bomarito, Miles Cranmer, Alcides Fonseca, Bogdan Burlacu, William G. La Cava, Fabrício Olivetti França (2025)

Preprint

arxiv.org  |  pdf

Recent Posts

Simplifying symbolic regression models without simplification rules

6 minute read

Relaxing the definition of equivalent mathematical expressions to get simpler and more interpretable models