Curriculum vitae

Main Research Areas
  • signal and data analysis
  • analysis of medical and microscopy images using computer vision approaches
  • statistical modeling and machine learning
Professional Career
since 2012 Postdoctoral researcher in the Applied Systems Biology group, Hans Knöll Institute, Jena, Germany.
2011-2012 Postdoctoral researcher in the group Computational Neuroscience and Machine Learning at Frankfurt Institute for Advanced Studies (FIAS) in Frankfurt am Main
2009-2011 Postdoctoral researcher in the Visual Neuroscience group at the School of Psychology at the University of Nottingham (GB)
2009 PhD in Applied Mathematics at the University of Nottingham (GB)
2005 M.Sc. in Engineering Physics at the Royal Institute of Technology in Stockholm (SWE)

Publications

Campagner A, Ciucci D, Svensson C-M, Figge MT, Cabitza F (2021) Ground truthing from multi-rater labeling with three-way decision and possibility theory. Inf Sci 545, 771-790.
Kästner B, Hengoju S, Svensson C-M, Figge MT, Rosenbaum MA (2021) Mit Tropfenmikrofluidik zu Hochgeschwindigkeits-Biotechnologie. BIOspektrum 27(3), 260-262. (Review)
Shopova IA, Belyaev I, Dasari P, Jahreis S, Stroe MC, Cseresnyés Z, Zimmermann AK, Medyukhina A, Svensson C-M, Krüger T, Szeifert V, Nietzsche S, Conrad T, Blango MG, Kniemeyer O, von Lilienfeld-Toal M, Zipfel PF, Ligeti E, Figge MT, Brakhage AA (2020) Human neutrophils produce antifungal extracellular vesicles against Aspergillus fumigatus. mBio 11(2), e00596-20.
Hirth G, Svensson C-M, Böttcher K, Ullrich S, Figge MT, Jungnickel B (2019) Regulation of the germinal center reaction and somatic hypermutation dynamics by homologous recombination. J Immunol 203(6), 1493-1501.
Kresinsky A, Schnöder TM, Jacobsen ID, Rauner M, Hofbauer LC, Ast V, König R, Hoffmann B, Svensson C-M, Figge MT, Hilger I, Heidel FH, Böhmer FD, Müller JP (2019) Lack of CD45 in FLT3-ITD mice results in a myeloproliferative phenotype, cortical porosity, and ectopic bone formation. Oncogene 38(24), 4773-4787.
Svensson C-M, Figge MT (2019) Künstliche Intelligenz für die biomedizinische Bildgebung. GIT Labor-Fachzeitschrift , (Review)
Svensson C-M*, Shydkiv O*, Dietrich S, Mahler L, Weber T, Choudhary M, Tovar M, Figge MT**, Roth M**; *authors contributed equally; *corresponding authors; **authors contributed equally (2019) Coding of experimental conditions in microfluidic droplet assays using colored beads and machine learning supported image analysis. Small 15(4), e1802384.
Tuchscherr L, Pöllath C, Siegmund A, Deinhardt-Emmer S, Hörr V, Svensson C-M, Figge MT, Monecke S, Löffler B (2019) Clinical S. aureus isolates vary in their virulence to promote adaptation to the host. Toxins 11(3), 135.
Allert S*, Förster TM*, Svensson C-M, Richardson JP, Pawlik T, Hebecker B, Rudolphi S, Juraschitz M, Schaller M, Blagojevic M, Morschhäuser J, Figge MT, Jacobsen ID, Naglik JR, Kasper L, Mogavero S, Hube B; *authors contributed equally (2018) Candida albicans-induced epithelial damage mediates translocation through intestinal barriers. mBio 9(3), e00915.
Svensson C-M, Medyukhina A, Belyaev I, Al-Zaben N, Figge MT (2018) Untangling cell tracks: Quantifying cell migration by time lapse image data analysis. Cytometry A 93(3), 357-370. (Review)