Ander Artola Velasco

Welcome! I’m Ander, a PhD. student at the Max Planck Institute for Software Systems, under the supervision of Dr. Manuel Gomez Rodriguez and as part of the IMPRS-TRUST program. Previously, I obtained my masters in Physics at Heidelberg University under the supervision of Dr. Sarah Bosman. I graduated in 2023 from the Complutense University of Madrid in Mathematics and Physics.

My primary (and past) interests include:

Machine learning, uncertainty quantification, explainability and support systems
Bayesian modelling and inference
Causality
Decision-making and strategic behavior
(Differential geometry and its applications)
(Cosmology, dark matter, the intergalactic medium and reionisation)
Anything that is intensive in abstract reasoning: from coding to philosophy

You can find my CV here.

news

May 29, 2025	Is your LLM overcharging you? In a newly released paper, we look at delegated text generation in LLMs from a game-theoretic point of view and show that tokenization has important implications when it comes to pricing models. We demonstrate that the current widely used scheme, which charges users per generated token, incentivizes providers of models to manipulate the information reported to the user. We further conduct experiments with multiple model families to demonstrate the feasibility of this strategic behavior and propose an alternative pricing mechanism that completely eliminates it. Our pre-print can be found here.
Feb 05, 2025	Our group at MPI-SWS has released a new joint paper on the evaluation of Large Language Models (LLMs). We use a causal framework to argue why controlling for the randomization in the generative process can be beneficial when evaluating models. It can be found here.
Dec 01, 2024	We have finally released the paper derived from my M.Sc. thesis on Bayesian Neural Networks applied to Warm Dark matter detection! You can find the pre-print here. It has also been submitted to Astronomy & Astrophysics.
Oct 10, 2024	I will be giving a talk at the Galaxy Coffee, the seminar of the “Galaxies & Cosmology” Department at the Max Planck Institute for Astronomy.
Oct 01, 2024	My master’s thesis is complete! Thanks to Heidelberg University (Institute for Theoretical Physics) and the Max Planck Institute for Astronomy. You can find it here. In this project, I use a Bayesian neural network to reconstruct the cosmic density fields from the Lyman-alpha forest. Based on those reconstructions, I constrain warm dark matter with unprecedented efficiency.