Vedrana Andersen Dahl

Vedrana Andersen Dahl

Associate Professor

Richard Petersens Plads

Building: 324, 250

2800 Kgs. Lyngby

Denmark

Phone: 45253078

Vedrana Andersen Dahl is developing methods for image analysis and geometry processing. Research interests include geometric texture analysis and synthesis, deformable models, texture based segmentation, OCT data, large tomographic data, feature preserving mesh smoothing, content aware geometry deformation.

CV

Education

2007 - 2011 PhD in Image Analysis and Computer Graphic - Technical University of Denmark, Department for Informatics and Mathematical Modelling
2005 - 2007 Msc in IT, Multimedia Technology - The IT University of Copenhagen
1992 - 1999 Diploma in Mathematics and Physics - University of Zagreb, Faculty of Science

Professional experience

2007 - 2010 PhD Student (IMM) - Technical University of Denmark, Institute for Informatics and Mathematical Modeling
1999 - 2001 Teacher of mathematics - Upper primary school Trnsko, Zagreb

Languages

English, Croatian, Danish
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  • IEEE

    United States

    BFI (2020): BFI-level 1

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  • Springer

    BFI (2020): BFI-level 1

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  • Springer Science+Business Media

    United States

    BFI (2020): BFI-level 1

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Activities

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  • Composites Science and Technology

    ISSNs: 0266-3538

    Pergamon Press, United Kingdom

    BFI (2020): BFI-level 2, Scopus rating (2018): CiteScore 6.63 SJR 1.796 SNIP 1.968, Web of Science (2020): Indexed yes, ISI indexed (2013): ISI indexed yes

    Central database

    Journal

  • Investigative Ophthalmology & Visual Science

    ISSNs: 0146-0404

    Additional searchable ISSN (Electronic): 0273-0189

    Association for Research in Vision and Ophthalmology, United States

    BFI (2020): BFI-level 2, Scopus rating (2018): CiteScore 3.21 SJR 1.933 SNIP 1.155, Web of Science (2020): Indexed yes, ISI indexed (2013): ISI indexed yes

    Central database

    Journal

  • Pattern Recognition Letters

    ISSNs: 0167-8655

    Additional searchable ISSN (Electronic): 1872-7344

    Elsevier, Netherlands

    BFI (2020): BFI-level 2, Scopus rating (2018): CiteScore 3.73 SJR 0.662 SNIP 1.64, Web of Science (2020): Indexed yes, ISI indexed (2013): ISI indexed yes

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