Kirsten Riber Philipsen works with modelling of complex stochastic dynamical systems; her focus is on mathematical models for the evolution of antibiotic resistance in bacteria populations and the spread of resistant bacteria between people in a human population. Antimicrobial resistance is a still increasing problem, which has limited the lifetime for antibiotic for treatments of humans as well as animals. This leads to a great need of developing new treatment methods or ways in which the resistance development can be delayed. Kirsten works on increasing the understanding of the evolution process through mathematical modelling and statistical analysis, especially using Stochatic Differential Equations. Kirsten Philipsen is experienced in working on cross-disciplinary projects with microbiologists, e.g. with design of experiments. Her research is part of a larger project titled "Evolution and adaptation of antimicrobial resistance in bacterial populations" (



2000 - 2006 Applied physics - Technical University of Denmark

Academic grades

MSc. Eng.

Professional experience

2006 - 2009 Ph.d. student (DTU Informatics) - Technical University of Denmark, Department of Informatics and Mathematical Modelling


Danish, English, Dutch (spoken)
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  • Journal of Theoretical Biology

    ISSNs: 0022-5193

    Additional searchable ISSN (Electronic): 1095-8541

    Academic Press, United Kingdom

    ISI indexed (2013): ISI indexed yes, BFI (2015): BFI-level 1, Scopus rating (2015): 1.089 0.982

    Local database


  • Journal of Microbiological Methods

    ISSNs: 0167-7012

    Additional searchable ISSN (Electronic): 1872-8359

    Elsevier BV, Netherlands

    ISI indexed (2013): ISI indexed yes, BFI (2015): BFI-level 1, Scopus rating (2015): 0.805 0.825

    Local database


  • Biometrics

    ISSNs: 0006-341X

    Additional searchable ISSN (Electronic): 1541-0420

    Wiley-Blackwell Publishing Ltd., United Kingdom

    ISI indexed (2013): ISI indexed yes, BFI (2015): BFI-level 2, Scopus rating (2015): 1.906 1.303

    Local database


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