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.

News

Jan 23, 2026	📑 First paper of the year! Can we improve protein domain annotation by combining sequence and 3D structure? Our new method, GNN2Pfam, uses Graph Neural Networks to outperform state-of-the-art HMMs in Pfam annotations: read the preprint here (to appear in Journal of Structural Biology.).
Oct 02, 2025	🏅 I’m honored to receive the ANCEFN incentive award for under 40 researchers in the area of Engineering Sciences!
Jun 25, 2025	📑 New paper! Can ML read emotions from physiology? In a big team competition, models beat random baselines but struggled with generalizability, revealing both the power and pitfalls of applying ML to affective science. Read here.
Apr 10, 2025	📑 New paper! Can RNA structure prediction benefit from large language models? Our study benchmarks 6 state-of-the-art RNA-LLMs across diverse datasets to find out: a short thread.
Apr 01, 2025	🧑‍🔬 PhD fellows joining the lab! Bruno Breggia will be working on improving representation learning for biological sequences, and Guillermo Kulemayer on joint generative models of sequence and structure