CAMPOS GARCIA, TONATIU

I am a researcher working at the intersection of plant biotechnology, computational biology, and cheminformatics. My research focuses on integrating experimental and computational approaches to understand biological systems and accelerate the discovery of bioactive molecules. I am particularly interested in the application of machine learning, molecular modeling, and metabolomics to investigate plant metabolism, microbial signaling, and the molecular mechanisms underlying chemical–biological interactions.

My work combines techniques such as molecular dynamics simulations, virtual screening, structural bioinformatics, and metabolomic analysis to explore metabolic responses and signaling pathways in plant systems, including model organisms such as Arabidopsis thaliana and cyanobacteria. Through these approaches, I aim to develop computational pipelines capable of analyzing complex biological data and identifying candidate molecules with potential applications in agriculture, biotechnology, and chemical biology.

In recent years, my research has increasingly focused on the development of AI-driven frameworks for chemical discovery and prioritization, including graph neural network models for virtual screening and the analysis of highly imbalanced chemical spaces. I am interested in bridging data-driven machine learning approaches with mechanistic insights from molecular modeling and quantum chemistry in order to improve interpretability and reliability in computational predictions.

More broadly, I am motivated by interdisciplinary research that connects plant biology, bioinformatics, and artificial intelligence to better understand metabolic networks and to support the discovery of biologically active compounds relevant to agriculture and biotechnology.