Teaching & Mentoring
I see teaching as part of training the next generation of researchers and practitioners in AI for healthcare. My teaching has focused on machine learning, deep learning, and applied health data science across undergraduate, master's, and professional settings. To date, I have contributed to **10 taught courses**, supervised **3 BSc theses** and **8 MSc theses**, and I currently **co-supervise 4 PhD students**.
Undergraduate Courses +
Bachelor Theses +
Bachelor Thesis, Bachelor in Data Science and Engineering, Universidad Carlos III de Madrid, 2023
Developing a Transformer based model, namely ShaftFormer, to characterise train driveshaft damages.
Bachelor Thesis, Bachelorstudium Medizininformatik, ZHAW School of Engineering, 2026
Bachelor thesis supervision in the Bachelorstudium Medizininformatik at the ZHAW School of Engineering.
Bachelor Thesis, Bachelorstudium Medizininformatik, ZHAW School of Engineering, 2026
Bachelor thesis supervision in the Bachelorstudium Medizininformatik at the ZHAW School of Engineering.
Master Programs +
Master course, Universidad Politécnica de Madrid, Master in Theoretical Signal Processing, 2024
Teaching assistant in the master course Bio Inspired Learning.
Master Theses +
Master Thesis, Master in Big Data Analytics, Universidad Carlos III de Madrid, 2023
Developing AI solutions, namely Recommender Systems such as NCF, to League of Legends pre-game winning team prediction.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2023
Developing Deep Learning models to predict antibiotic-resistant bacteria in multi-domain datasets.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2023
Developing a unsupervised generative models, namely VAEs, to clusterise temporal bacteriological strains.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2024
Developing a dual-branch recommender system for antibiotic recommendations over bacterial strains.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2024
Developing a AT techniques to make microbiology AI more robust.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2024
Condition diffusion models on EEG to generate speech.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2025
Developing an automatic classifier of fungi species based on their MALDI-TOF MS data for hospital purposes.
Master Thesis, Master in Applied Artificial Intelligence, Universidad Carlos III de Madrid, 2025
Developing an automatic unsupervised domain adaptation of MALDI-TOF MS inter-hospitalary.
PhD Co-supervision +
PhD co-supervision, Institute of Medical Microbiology, University of Zurich, 2025
Co-supervising Eline Meijer’s PhD project on boosting the resolution of MALDI-TOF mass spectra using transformer-based machine learning.
PhD co-supervision, Institute of Medical Microbiology, University of Zurich, 2025
Co-supervising Yukino Gütlin’s PhD project on predicting antimicrobial resistance, virulence, and invasiveness from MALDI-TOF MS data to support antimicrobial treatment decisions.
PhD co-supervision, Institute of Medical Microbiology, University of Zurich, 2025
Co-supervising Janis Rogenmonser’s PhD project on advancing antimicrobial resistance prediction from whole-genome sequencing.
Corporate Training +
Corporate training, Fundación Carlos III de Madrid, 2022
I teach Corporate Training to BBVA bank employees three times a year since 2022. Specifically, a course in Machine Learning Fundamentals.