I am a CFIS student pursuing a double degree in Data Science and Biomedical Engineering at Universitat Politècnica de Catalunya (UPC). My interests lie in developing new Machine Learning methods for biology and healthcare, combining technical and biomedical expertise to drive impactful research.
Research Intern (visiting student)
Massachusetts Institute of Technology (Uhler Lab)
July 2025 - Present
Working on Statistical Optimal Transport for genetic data. In person from February 2026
ML Engineering Intern
Esperanto Technologies, Mountain View, USA
July 2024 - September 2024
Researched and implemented KV Cache compression methods for LLMs, including quantization and eviction-based approaches, to improve inference efficiency.
ML Engineering Intern
Esperanto Technologies, Barcelona, Spain
July 2023 - August 2023
Implemented diffusion models into the company's software stack, gaining deep algorithmic and theoretical insight into their operation.
Research Intern
Center for Research of Biomedical Engineering (CREB)
July 2022 - August 2022
Applied Deep Learning for survival analysis, focusing on a clinical use case. Gained familiarity with Transformers, RNNs, and Cox Proportional Hazards Models.
BSc in Data Science and Engineering (GPA: 9.27/10)
BSc in Biomedical Engineering (GPA: 9.32/10)
Universitat Politècnica de Catalunya (UPC) - CFIS Center for Interdisciplinary Studies
2021 - 2026 (Expected)
Teaching Assistant
Universitat Politècnica de Catalunya (UPC)
February 2024 - June 2024
Provided assistance on the Mathematical Optimization subject of the degree in Data Science and Engineering.
Vice President of the Ecologic Association (EcoEEBE)
Universitat Politècnica de Catalunya (UPC)
2023 - 2024
Coordinated actions, including nature outings and cultural activities, to promote environmental awareness.
Student Mentor
Spanish and Iberoamerican Biology Olympics
2023
Accompanied and supported students during the national and iberoamerican phases of the competition.
Organizer
Nabój Junior Competition
2022
Helped with the translation of problems for the European-level math and physics competition.
Developed an LLM RAG application to create video clips from a user's image gallery based on a text prompt, complete with AI-generated background music. [Details]
Cleaned and processed raw delivery data, then built and fitted logistic regression and transformer-based models to predict supply chain delays. [GitHub]
Developed a convolutional neural network to classify chest X-ray images. This work received an Honorific Mention in the UPF Awards to Research Projects. [Full Report]