Scholar
Francisco N. F. Q. Simoes
Google Scholar ID: OxSsOmsAAAAJ
PhD student, Utrecht University
Citations & Impact
Citations
16
H-index
2
i10-index
0
Publications
6
Co-authors
3
list available
Publications
Resume (English only)
Academic Achievements
- - 'The Minimal Search Space for Conditional Causal Bandits', submitted to ICLR 2026
- - 'The Causal Information Bottleneck and Optimal Causal Variable Abstractions', accepted for UAI 2025
- - 'Fundamental Properties of Causal Entropy and Information Gain', CLeaR 2024 conference
- - 'Causal Entropy and Information Gain for Measuring Causal Control', ECAI 2023 conference
- - 'Jaccard Kernel PCA in genotype and gene-burden data for ALS', Internship report, supervisor: Kevin Kenna
Research Experience
- - PhD candidate, Department of Information and Computing Sciences, Intelligent Systems group, Utrecht University, in collaboration with ProRail, 2021-Now
- - ML engineer & Data Scientist, Orbisk (Utrecht), 2020-2021, Computer Vision, API development
- - Research internship at UMC's Brain Center, 2020, Dimensionality reduction methods in a Genome-Wide Association Study (GWAS) of ALS
Education
- - PhD in Artificial Intelligence, Utrecht University, 2021-Now
- - MSc in Theoretical Physics, Utrecht University, 2017-2019, Mathematical emphasis: Lie Algebras, Differential Geometry, Representation Theory, etc.
- - A la carte Mathematics units, University of Porto, 2016-2017, Topology, Group Theory, Logic, Functional Analysis, Manifolds, etc.
- - BSc in Physics, University of Porto, 2013-2016
Background
- Research interests: causal inference, intervention selection, representation learning, information theory. Current research focuses on constructing useful abstractions from data using the interventionist framework of causal inference. The goal is to develop algorithms that learn abstractions with desired properties using appropriate information-theoretic metrics.
