Chemistry Publications

These are my published research outputs. I'll be happy to discuss these further via email.

My work centers on predictive inverse design and machine learning (ML) for chemistry under realistic constraints. I specialize in inverse/generative molecular design, cheminformatics, and transformer models for SMILES/RDKit workflows and reaction-data analytics. Among others, I developed a supervised ML model for predicting vanadium-catalyzed epoxidation yields, an explainable model for predicting solvation Gibbs energy, and an inverse, de novo generative model for designing vanadyl-based epoxidation catalyst ligands across a large, curated chemical space.

Data Driven Chemistry

♦ Inverse ligand design: a generative data-driven model for optimizing vanadyl-based epoxidation catalysts (with Filipe Teixeira, M. Natália D. S. Cordeiro and Tomoyuki Miyao) • Journal of Catalysis (2026) Publisher Site PDF