I'm Gabriel Budel — also known as Gaby Budel — an Applied Scientist at Uber with a Ph.D. in Artificial Intelligence and Network Science from TU Delft. My Ph.D. research focused on embeddings of complex networks and the roles of complementarity and similarity in these embeddings, with applications to semantic networks and NLP. My interests include artificial intelligence, machine learning, causal inference, hyperbolic graph embeddings, deep learning, and NLP.
Publications
2024
2024
2023
Topological properties and organizing principles of semantic networks.
Budel, G., Y. Jin, P. Van Mieghem, and M. Kitsak.
Nature Scientific Reports 13(1), 11728.
doi
2020
Detecting the number of clusters in a network.
Budel, G. and P. Van Mieghem.
Journal of Complex Networks 8(6), cnaa047.
doi
2018
Predicting user flight preferences in an airline E-shop.
Budel, G., L. Hoogenboom, W. Kastrop, N. Reniers, and F. Frasincar.
In: Mikkonen T., Klamma R., Hernández J. (eds)
Web Engineering. ICWE 2018. Lecture Notes in Computer Science, vol 10845. Springer, Cham.
doi
Working Papers
2026
Complementarity in Complex Networks.
Budel, G. and M. Kitsak.
arXiv:2003.06665
code
Ph.D. Thesis
2024
Complementarity and Similarity in Complex Networks.
Budel, G.J.A.
doi
Presentations
2023
Complementarity vs. Similarity in Semantic Networks
2021
Random Hyperbolic Graphs in d + 1 Dimensions
2018
Predicting User Flight Preferences in an Airline E-Shop
Software
2025
Complementarity-based HyperLink Embedder
bitbucket
2022
RHG Generator
bitbucket
2018
DBHC
cran
2018
FX Trading NEAT
github
Experience
2025–
Scientist
2023–25
Data Scientist
2019–23
Ph.D. Researcher
Education
2019–24
Ph.D. in Artificial Intelligence and Network Science
2018–19
Advanced Language Program Mandarin Chinese
2017–18
M.Sc. in Finance & Investments
2016–18
M.Sc. in Econometrics & Management Science
2013–16
B.Sc. in Econometrics & Operations Research