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Kristian Hovde Liland
  • Førsteamanuensis
    • Fakultet for realfag og teknologi
    • Institutt for maskinteknikk og teknologiledelse
+4767231624
kristian.liland@nmbu.no
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In 2017 dr Liland was employed as a top scientist in data science at the faculty of Science and Technology where he is currently developing courses and lecturing, supervising master and PhD students, and conducting research in method development and applications.

He has previously been working as a researcher at Nofima for 5.5 years and in various positions at NMBU/KBM for a dozen years, and he still enjoys a close colaboration with both.

 

  • Fagfelt
    • Multivariate data analysis
    • Background correction / Pre-processing
    • Machine Learning / Deep Learning
    • Software development for data analysis
  • Publikasjoner
    Liste med publikasjoner fra min forskning. (Cristin)

    Curriculum Vitae (external link)

  • Undervisning

    Courses I am involved in.

  • Forskning & prosjekt

    Prosjekter

    Biofuel production from fish waste using data mining and data modeling for optimal catalyst selection.
    Using big data to select the best catalytic materials to transform fish waste into valuable chemicals.

    Data driven approach for prediction of power flexibility
    The expected outcome of this project is to develop a methodology for prediction and trading of power flexibility, including the development of new business models for future flexibility markets.

    Forskningsområder

    Tema: 

    • Teknologi

    Spesialområder: 

    • Datavitenskap;Statistikk;Maskinlæring;Spektroskopi
  • Annet & CV

    Kristian's research profiles:
    ResearchGate
    Google Scholar
    Orcid
    Mendeley

    Kristian's program packages in R and Python:
    GitHub
    R Documentation

    Relevant formal background in: informatics, mathematics and applied statistics.

    Typical application areas are within:
    - food and raw material analyses,
    - spectroscopy and spectrometry for quantification and classification,
    - hyperspectral image analysis,
    - various omics analyses, 
    - etc.

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