Adrián Arnaiz-Rodríguez
PhD Student
Adrián Arnaiz Rodríguez is an ELLIS PhD student. He holds a Bachelor’s degree in Computer Engineering (2019, Universidad de Burgos) and a Master’s degree in Data Science and Artificial Intelligence (2021, Universitat Oberta de Catalunya). His PhD topics are AI Fairness and Graph Theory to enhance ethics, accountability, and transparency in algorithmic decision-making. His supervisors are Nuria Oliver (ELLIS Alicante), and Manuel Gómez Rodríguez (Max Planck Institute for Software Systems).
Website: https://adrian-arnaiz.netlify.app
Link to ORCID profile: https://orcid.org/0000-0001-5567-801X
Publications in association with ELLIS Alicante
2024
10/05
Schweighofer, K.,
Arnaiz-Rodríguez, A.,
Hochreiter, S.,
&
Oliver, N.
(2024).
The Disparate Benefits of Deep Ensembles.
arXiv:2410.13831.
03/06
Arnaiz-Rodríguez, A.,
Curto, G.,
&
Oliver, N.
(2024).
Structural Group Unfairness: Measurement and Mitigation by means of the Effective Resistance.
WWW 2024 Workshop on Trustworthy Learnin on Graphs (TrustLOG).
03/06
Arnaiz-Rodríguez, A.,
&
Oliver, N.
(2024).
Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values.
ICLR 2024 Workshop on Data-centric Machine Learning Research (DMLR).
2023
05/05
Curto, G.,
Arnaiz-Rodríguez, A.,
&
Oliver, N.
(2023).
Algorithms for Social Justice: Affirmative Action in Social Networks.
arXiv:2305.03223.
03/03
Arnaiz-Rodríguez, A.,
Escolano, F.,
&
Oliver, N.
(2023).
FairShap: A Data Re-weighting Approach for Algorithmic Fairness based on Shapley Values.
arXiv:2303.01928.
2022
12/21
Arnaiz-Rodríguez, A.,
Begga, A.,
Escolano, F.,
&
Oliver, N.
(2022).
DiffWire: Inductive Graph Rewiring via the Lovász Bound.
Proceedings of the First Learning on Graphs Conference, PMLR, 198, 15:1-15:27.
01/31
Olivares Gil, A.,
Arnaiz Rodríguez, A.,
Ramírez Sanz, J. M.,
Garrido Labrador, J. L.,
Ahedo García, V.,
García Osorio, C.,
Santos Martín, J. I.,
&
Galán Ordax, J. M.
(2022).
Mapping the scientific structure of organization and management of enterprises using complex networks.
International Journal of Production Management and Engineering, 10(1), 65-76.