Leandro A. Bugnon

My research goal is to develop AI methods that decode the language of biology, enabling faster drug discovery, better disease diagnostics, and deeper understanding of molecular mechanisms.

I work at the intersection of AI and bioinformatics, with a focus on learning representations of biological sequences, RNA structure prediction, and conditional generative models.

I am an Associate Researcher at sinc(i)/UNL – CONICET, and an Associate Professor at the National University of the Litoral and Austral University. I also collaborate with The Cell Company on applied bioinformatics projects.

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2026

[DOI]

ET-Pfam: ensemble transfer learning for protein family prediction

Duarte, Vitale, Escudero et al. · Bioinformatics 42(4)
2026

[DOI]

GNN2Pfam: Integrating protein sequence and structure with graph neural networks for Pfam domain annotation

Fenoy, Bugnon, Vitale et al. · Journal of Structural Biology 218(1)
2025

[DOI]

Big team science reveals promises and limitations of machine learning efforts to model physiological markers of affective experience

Coles, Perz, Behnke et al. · Royal Society Open Science 12(6)

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2026-04 BioComputingUP @ Università di Padova (IDPfun2) · linker characterization 2025-12 Profesor Adjunto · UNL 2025-12 Associate Researcher · CONICET 2025-10 ANCEFN incentive · Engineering, <40 2025-04 B. Breggia + G. Kulemayer · sequence representations, joint seq/structure generative models

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