Ph.D. student
Through my educational background and previous work I have specialized in advanced machine learning and statistical modelling of neuroimaging data, in particular functional magnetic resonance imaging (fMRI).
Furthermore, I have a profound interest in Bayesian statistics as well as model development and validation.
Computational Neuroimaging
fMRI
Brain Stimulation
2016
MSc. Neuroscience and Neuroimaging, Aarhus University & Chinese Academy of Sciences (UCAS)
2014
BSc. in Engineering, Biomedical Engineering, Technical University of Denmark
2017 - Present
Ph.D. student, DRCMR
2016 - 2017
Research Assistant, DRCMR
2011 - 2014
Student Counselor, Technical University of Denmark (DTU)
2013 - 2014
Teaching and presentation development, LearningLab DTU
Madsen, K. H., Krohne, L. G., Cai, X-L., Wang, Y. & Chan, R. C. K.
Perspectives on Machine Learning for Classification of Schizotypy Using fMRI Data.
Schizophrenia Bulletin (2018).
Krohne, L. K. & Madsen, K. H.
Functional Connectivity during Theory of Mind and Empathy tasks, using Machine Learning in Subjects with Schizotypy. 131 p., 2016.
Krohne, LK, Hansen, RB, Christensen, JAE, Sorensen, HBD & Jennum, P ’Detection of K-complexes based on the wavelet transform’ IEEE Engineering in Medicine and Biology Society. Conference Proceedings, vol. 2014, pp. 5450-5453.