Education
MSc in Machine learning, Data Science and Artificial Intelligence — Aalto University, Finland
September 2022 - September 2024
GPA of 5.0 out of 5.0 (max. grade in all courses). Received the Dean's Scholarship for outstanding academic performance.
BSc Computer Science — University College London, UK
September 2016 - June 2019
First Class (1:1) grade. Minor in Entrepreneurship.
Professional Experience
PhD Candidate — University of Tübingen, Max Planck Institute for Intelligent Systems, ELLIS
June 2025 - Present
Advised by Prof. Matthias Bethge (BethgeLab) and Prof. Tim Rocktäschel (UCL DARK, Recursive).
Research Assistant — Intelligent Robotics Group, Aalto University
May 2023 - August 2023
Supervised by Prof. Ville Kyrki and Prof. Kevin Luck. Culminated in the paper "Co-Adaptation of Embodiment and Control with Self-Imitation Learning", accepted at IROS 2025 and winning the Best Workshop Paper Award at RSS EARL 2024.
Backend Software Engineer — Cabify
January 2022 - August 2022
Cabify is a Spanish ride-sharing company which provides vehicles for hire via its smartphone mobile app. It was the first Spanish unicorn. I worked on Cabify’s matching algorithms, which are used to match incoming riders’ journey requests and suitable drivers.
Content Systems Engineer — Rockstar Games
November 2020 - June 2021
I designed and developed software systems for Rockstar’s large and highly complex virtual game environments to enable the creation of gameplay content for their titles.
Technology Consultant — PwC
May 2019 - October 2020
I mainly worked on two areas: software engineering (~80%) and foreign direct investment (FDI) attraction on the high-tech sector (~20%).
Student Partner — Microsoft
April 2018 - April 2019
Academic Tutor — UCL Department of Computer Science
September 2017 - April 2018
Vocational
Reviewer — ICLR Workshop RSI
February 2026
Courses (non-exhaustive)
Graduate
- Statistical NLP
- Reinforcement Learning
- Nonlinear Optimization
- Deep Learning
- Research Project in ML
- Gaussian Processes
- Supervised Methods
- Bayesian Data Analysis
- Data Mining
- Federated Learning
- Computer Vision
- Seminar in CS
Undergraduate
- Discrete Mathematics
- Mathematics & Statistics
- Computer Architecture & Concurrency
- Computability & Complexity Theory
- Logic & Database Theory
- Machine Learning for Behavioral Analytics
- Computer Systems
- Robotics Programming
Certifications
Machine Learning — Stanford University (Coursera)
September 2018
Skills
Most used programming languages
Python, C/C++, Lua, Go, web (Vue, React, CSS).
Libraries
Numpy, PyTorch, VeRL, Gym-style environments, Matplotlib, Pandas, W&B...
Other technologies
Docker, Git, multi-node SLURM clusters, Linux/Unix.
Languages
Native Spanish and bilingual proficiency in English.