Scholar
Kim Steenstrup Pedersen
Google Scholar ID: RzH2vKQAAAAJ
Department of computer science, University of Copenhagen
Citations & Impact
Citations
748
H-index
12
i10-index
13
Publications
20
Co-authors
46
list available
Publications
Resume (English only)
Academic Achievements
- Has several research collaborations with partners from industry, including FOSS Analytics and the ClimbAlong sports analytics project with NorthTech ApS.
Research Experience
- From 2003 to 2006, he was an assistant professor at the IT University of Copenhagen, Denmark. Currently, he is a full professor jointly at DIKU and the Natural History Museum of Denmark (NHMD). He was the vice head of department for teaching from 2009 to 2012 at DIKU and the Head of the research section for Image Analysis, Computational Modelling, and Geometry (IMAGE) at DIKU. He is also the co-founder, co-owner, and CTO of DigiCorpus ApS, which develops computer vision-based tools for aiding physiotherapy. He is currently the Head and Curator of Digital Collections at NHMD and the GBIF Head of Delegation for Denmark.
Education
- Received his M.Sc. degree in 1999 and Ph.D. degree in 2003, both in Computer Science from the Department of Computer Science (DIKU), University of Copenhagen, Denmark. He also holds a B.Sc. degree in Physics from the University of Copenhagen. During his Ph.D. studies, he spent half a year in the spring of 2001 at the Division of Applied Mathematics, Brown University, Rhode Island, USA.
Background
- Primary research interests include computer vision, image analysis, and machine learning, especially object recognition and detection, tracking and motion models, stochastic image models, and natural image statistics. He has made contributions to the theoretical foundations of low-level vision, including applications of machine learning to low-level vision, scale space theory, articulated tracking of human motion, and image features and their applications. Current research activities include: phenotyping of pinned insects by learning morphological traits from specimen images and combining with molecular data such as selected genes; refractive multi-view 3D reconstruction; deep learning methods incorporating domain-specific knowledge for hyperspectral images.
Miscellany
- Email: kimstp@di.ku.dk / kimstp@snm.ku.dk; Phone: (+45) 61 37 45 29; GitHub: github.com/kimstp; ORCID: 0000-0003-3713-0960; Google Scholar: RzH2vKQAAAAJ; LinkedIn: kimstp; DBLP: Profile; OpenReview: ID: ~Kim_Steenstrup_Pedersen1; ReSearcher.cc: Profile; ResearcherID: L-8748-2016; WikiData: Q28601608
