Bruno Trentini
Bruno Trentini
Interests
Foundational Machine Learning, Differential Geometry, Information Theory, Dynamic Systems, Biology, Chemistry, AI for Science
Biography
Bruno Trentini is a doctoral student in the Computer Science Department at the University of Oxford. His research focuses on foundational machine learning for dynamic systems, particularly in biology and chemistry. His interests span generative modeling, information theory, differential geometry, and protein dynamics. He is also a full-time researcher on NVIDIA’s Digital Biology team 🌎 https://trentini.fyi/
Selected Publications
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Advancing Protein Ensemble Predictions Across the Order–Disorder Continuum
Kamil Tamiola Michele Invernizzi Sandro Bottaro Julian O Streit Bruno Trentini Niccolò Alberto Elia Venanzi Danny Reidenbach Youhan Lee Christian Dallago Hassan Sirelkhatim Bowen Jing Fabio Airoldi Kresten Lindorff−Larsen Carlo Fisicaro
2025.
Details about Advancing Protein Ensemble Predictions Across the Order–Disorder Continuum | BibTeX data for Advancing Protein Ensemble Predictions Across the Order–Disorder Continuum | Link to Advancing Protein Ensemble Predictions Across the Order–Disorder Continuum
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Improving Inverse Folding for Peptide Design with Diversity−Regularized Direct Preference Optimization
Ryan Park Darren J. Hsu Chen Tessler Maria Korshunova C. Brian Roland Shie Mannor Olivia Viessmann Bruno Trentini
2024.
Details about Improving Inverse Folding for Peptide Design with Diversity−Regularized Direct Preference Optimization | BibTeX data for Improving Inverse Folding for Peptide Design with Diversity−Regularized Direct Preference Optimization
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ML for Life and Material Science: From Theory to Industry Applications (ICML 2024 Workshop)
Aviv Regev Andrea Volkamer Bruno Trentini Cecilia Clementi Charles Harris Charlotte Deane Christian Dallago Ellen D Zhong Francesca Grisoni Jinwoo Leem Kevin K Yang Marwin Segler Michael Martin Pieler Nicholas James Sofroniew Olivia Viessmann Peter K Koo Pranam Chatterjee Puck Van Gerwen Rebecca K. Lindsay Umberto Lupo Ying Wai Li
In ICML Workshops. 2024.
Details about ML for Life and Material Science: From Theory to Industry Applications (ICML 2024 Workshop) | BibTeX data for ML for Life and Material Science: From Theory to Industry Applications (ICML 2024 Workshop)