Aaron Weimann
Aaron Weimann

Senior Research Associate

About me

I am a postdoctoral scientist specializing in computational biology, with a strong focus on bacterial genomics. My expertise lies in developing and applying AI/ML-driven tools to analyse genomic patterns that influence bacterial pathogen behaviour, including antimicrobial resistance and virulence.

In recent years, my research has concentrated on Pseudomonas aeruginosa. Collaborating with academic and industry partners worldwide, we have put together and utilized the largest data collection globally to map the evolution of this bacterium. Our groundbreaking findings have revealed significant insights into how Pseudomonas aeruginosa has evolved and adapted to the human environment, with important implications for clinical practice.

Interests
  • Microbiology
  • Infectious diseases
  • Evolutionary biology
  • Phylogenetics
  • Statistical genomics
  • Machine learning and AI
Education
  • PhD Computer Science, 2017

    Heinrich Heine University of Duesseldorf

  • MSc Bioinformatics, 2010

    Saarland University

  • BSc Bioinformatics, 2008

    Saarland University

My affiliations
  • Postdoctoral fellow, VPD Heart and Lung Research Institute, University of Cambridge with Professor Andres Floto
  • Postdoctoral associate, Cambridge Center of AI in Medicine (CCAIM)
  • Visiting postdoctoral fellow, University of Cambridge Veterinary School with Professor Julian Parkhill
  • Visiting postdoctoral fellow, Wellcome Trust Sanger Institute with Professor Nicholas Thomson
Featured Publications
Recent Publications
(2024). Evolution and host-specific adaptation of Pseudomonas aeruginosa. Science.
(2024). Sequence-based modelling of bacterial genomes enables accurate antibiotic resistance prediction. bioRxiv.
(2023). Impact of transient acquired hypermutability on the inter- and intra-species competitiveness of Pseudomonas aeruginosa. ISME J..
(2023). Mutational spectra are associated with bacterial niche. Nat. Commun..
(2022). Mycobacterium abscessus pathogenesis identified by phenogenomic analyses. Nat Microbiol.