Research group
High Performance Computing in Molecular Modelling
Position
PhD student
José is a Portuguese data-driven chemist, historian and philosopher of science. He has a Ph.D. from the MIT-Portugal Program at the LAQV-REQUIMTE Laboratory, University of Porto, where he develop Data Science and Artificial Intelligence (AI) methods to predict chemical properties and reaction yields. He received two visiting scholar appointments during his Ph.D. in Sustainable Chemistry, at the MIT Department of Chemical Engineering (USA) and at the NAIST (Nara Institute of Science and Technology) Data-Driven Chemistry Lab (Japan). He was also a Fulbright scholar at the University of California, Irvine (USA) on a project on using computational models to study disinformation and scientific knowledge. José has also collaborated with the Institute of Contemporary History at the University of Évora, focusing on the role of chemistry in scientific regulation, actively participating in organizations such as the SPQ History of Chemistry Group, the International Younger Chemists Network and the European Society for the History of Science.
Personal website: https://www.jfcaetano.com
Representative Publications
Navigating epoxidation complexity: building a data science toolbox to design vanadium catalysts
10.1039/d3nj05784d
Optimizing Vanadium-Catalyzed Epoxidation Reactions: Machine-Learning-Driven Yield Predictions and Data Augmentation
10.1021/acs.jcim.5c01104
Inverse ligand design: a generative data-driven model for optimizing vanadyl-based epoxidation catalysts
10.1016/j.jcat.2025.116537
AutoVap: An Interactive Machine Learning Tool for Predicting the Standard Enthalpy of Vaporization
10.1002/cite.70111
