Dr. Manuel Borja has a background in statistics and natural sciences and works at the intersection of machine learning and pharmaceutical manufacturing. His research focuses on developing machine learning approaches to support drug product formulation and manufacturing, with the aim of improving process understanding and optimization. His research, carried out in collaboration with Johnson & Johnson Innovative Medicine, explores methods that integrate expert knowledge into machine learning algorithms, including human-in-the-loop approaches that combine data-driven models with domain expertise to assist decision-making in pharmaceutical process development.
Interests
- ML applications in Pharmaceutics
- Mathematical Optimization
- Statistical Analysis
Education
-
Post-doctoral research fellow,
2026 - Ongoing
Ghent University (UGent) -
PhD in Bioscience Engineering - Mathematical Modelling,
2021 - 2026
Ghent University (UGent) -
MSc in Statistics and Data Science,
2021
KU Leuven -
BSc in Physics,
2018
Universidad Complutense / Madrid
