About
About me
I'm a PhD candidate in the Hertie Institute for AI in Brain Health at the University of Tübingen. I build machine learning methods that turn large, messy datasets into representations people can explore and reason about.
I fine-tune transformer-based LLMs to produce text embeddings that capture semantic meaning, and I adapt dimensionality reduction methods like t-SNE and UMAP to scale to millions of data points. I used these methods to build a map of 21 million biomedical publications. This map reveals trends in how research fields grow and change over time.
I'm interested in bringing that same skill set to applied, industry-scale problems. This means turning large amounts of high-dimensional data into something usable, and using LLMs and agents to help solve real-world tasks.
I'm currently on the job market for machine learning engineer / applied scientist roles in industry, starting autumn.
Education
PhD Machine Learning
2022 - present
Berens Lab, Hertie Institute for AI in Brain Health
International Max Planck Research School on Intelligent Systems
University of Tübingen
MSc Neural Information Processing
2019 - 2021
University of Tübingen
International Max Planck Research School
BSc Physics
2015 - 2019
University of Sevilla
University of Münster
BSc Materials Engineering
2015 - 2018
University of Sevilla
parallel studies, not finished
Skills
Machine learning
Technical skills
Languages
Spanish (native)
English (proficient)
German (advanced knowledge)