Postdoctoral Researcher at InSiliChem, Universitat Autònoma de Barcelona
PhD in Computational Drug Discovery · AI and physics-based molecular modelling

• Now: predicting P450 metabolism, and building open tools for computational drug discovery (BioLatent, Assayer).
• Research interests: natural products, neurodegenerative diseases and antimicrobial resistance.
• Learning: free energy perturbation and umbrella sampling.
• Open to collaborations on in silico drug design, QSAR, docking and molecular dynamics. Email me.

Assayer · assayer.vercel.app
A catalogue of 2,000+ medicinal and computational chemistry tools (300 curated by hand), plus step-by-step protocols that say which tools to use at each step and what it has to prove before you move on.

BioLatent · biolatent.vercel.app
A registry and benchmark of molecular, protein and nucleic-acid representations. Version 1.1.0 compares 18 frozen representations across 9 tasks under one prespecified protocol.

Sorbent
A compound triage service built on FastAPI and RDKit. Submit a SMILES library, get back a ranked, deduplicated, liability-flagged shortlist where every number is deterministic and citable.

Learn CADD · learn-cadd.vercel.app
An interactive, first-principles course on computer-aided drug design: 18 modules, each pairing theory with a browser playground.

Awesome Drug Discovery
A curated resource list on computational methods for drug discovery.

• QSARBoost: a Python framework for building, validating and applying gradient boosting QSAR models.
• QSARBioPred: a Jupyter notebook for building QSAR classification models for bioactivity prediction.
• EnsembleBBB: an ensemble machine learning model for predicting blood-brain barrier permeability.
• VinaScreen: an automated AutoDock Vina script for structure-based virtual screening.
• GMXPlotter: a reproducible analysis workflow for GROMACS MD simulations on Google Colab.
• CoumarinDB and ArtemisiaDB: curated databases of naturally occurring coumarins and of secondary metabolites from Artemisia species.
• comp_chem_colab: Jupyter notebooks for computational chemists.

Cheminformatics and ML: Python, RDKit, scikit-learn, PyTorch, Hugging Face Transformers
Simulation and docking: GROMACS, AutoDock Vina
Software: FastAPI, Next.js, TypeScript, Jupyter, Linux, Bash

Recent papers are listed on my website and Google Scholar.