Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Lecturer in Biomathematics







Huxley BuildingSouth Kensington Campus





Barbara Bravi obtained her PhD in Applied Mathematics (Biological and Statistical Physics) at King’s College London under the supervision of Peter Sollich, working on path integral approaches to subnetwork description and inference for biochemical stochastic processes. She was then postdoctoral researcher at École Politechnique Fédérale de Lausanne (supervised by Matthieu Wyart) and subsequently at École Normale Supérieure de Paris (supervised by Simona Cocco, Rémi Monasson, Thierry Mora, Aleksandra Walczak). In her postdoctoral research, she investigated and developed statistical frameworks of inference to model different examples of protein functions: protein allostery, i.e., the regulation between distant sites in proteins (at École Politechnique Fédérale de Lausanne); the protein-protein binding mechanisms underlying immune responses at the molecular level (at École Normale Supérieure de Paris). She joined the Department of Mathematics as Lecturer in Biomathematics in October 2021.

Barbara’s research focusses on statistical inference methods for biological systems, in particular methods to reconstruct dynamics of biological networks and the sequence-function mapping in proteins; currently, an area of particular interest to her is immunology. More broadly, Barbara’s research directions include: mathematical modelling of stochastic biochemical reactions and model reduction strategies for complex networks; machine learning, data science and their biomedical applications.

Enquiries from prospective PhD students are welcome.



Bravi B, 2024, Development and use of machine learning algorithms in vaccine target selection., Npj Vaccines, Vol:9

Bravi B, Di Gioacchino A, Fernandez-de-Cossio-Diaz J, et al., 2023, A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity., Elife, Vol:12

Meysman P, Barton J, Bravi B, et al., 2023, Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report, Immunoinformatics, Vol:9, ISSN:2667-1190, Pages:1-8

Łuksza M, Sethna ZM, Rojas LA, et al., 2022, Neoantigen quality predicts immunoediting in survivors of pancreatic cancer., Nature, Vol:606, ISSN:0028-0836

Bravi B, 2021, il sistema immunitario attraverso la lente dell'inferenza statistica, Ithaca: Viaggio Nella Scienza, Vol:18, ISSN:2282-8079

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