João Mota

Contributed to the validation of a deep learning–based synthetic data generation model (TTVAE-MMD) developed by the research team. Evaluated the quality and statistical consistency of generated medical datasets to assess their suitability for downstream machine learning tasks. Supported model assessment through structured experimentation and performance analysis in healthcare data contexts.

Engineering Internship at Fraunhofer Portugal AICOS (2026-01 – 2026-02)

• Contributed to the validation of a deep learning–based synthetic data generation model (TTVAE-MMD) developed by the research team.
• Evaluated the quality and statistical consistency of generated medical datasets to assess their suitability for downstream machine learning tasks.
• Supported model assessment through structured experimentation and performance analysis in healthcare data contexts.

Machine Learning and Deep Learning – Stanford University and DeepLearning.AI (2025-06 – 2025-08)

Python – CS50 Harvard (2025-01 – 2025-04)

BSc in Biomedical Engineering – Nova FCT (2023-09 – 2026-07)

Artificial Intelligence – Samsung Innovation Campus (2025-10 – 2026-03)