World's Best Scientists 2026 revealed!
Award Badge
Computer Science
Denmark
2026

D-Index & Metrics

Computer Science

D-Index
68
Citations
25762
World Ranking
2039
National Ranking
8

Research.com Recognitions

  • 2026 - Research.com Computer Science in Denmark Leader Award
  • 2025 - Research.com Computer Science in Denmark Leader Award
  • 2023 - Research.com Computer Science in Denmark Leader Award
  • 2022 - Research.com Computer Science in Denmark Leader Award

Overview

Lars Kai Hansen is affiliated with the Technical University of Denmark in Denmark. Their research primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, and Atomic and Molecular Physics and Optics.

The scientist's recent publications cover a range of interdisciplinary topics and venues. Notable papers include:

  • Using sequences of life-events to predict human lives, 2023, Nature Computational Science
  • A machine-learning framework for robust and reliable prediction of short- and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data, 2020, Translational Psychiatry
  • Mycoplasma pneumoniae incidence, phenotype, and severity in children and adolescents in Denmark before, during, and after the COVID-19 pandemic: a nationwide multicentre population-based cohort study, 2024, The Lancet Regional Health - Europe
  • Noise-assisted variational quantum thermalization, 2022, Scientific Reports
  • Clinical progression, disease severity, and mortality among adults hospitalized with COVID-19 caused by the Omicron and Delta SARS-CoV-2 variants: A population-based, matched cohort study, 2023, PLoS ONE

The frequent publication venues for their work include arXiv (Cornell University), PLoS ONE, Zenodo (CERN European Organization for Nuclear Research), Nature Computational Science, and The Lancet Regional Health - Europe.

The scientist collaborates with a number of frequent co-authors, including:

  • Lenka Tětková
  • Jonathan Foldager
  • Teresa Karen Scheidt
  • Karen S. Ambrosen
  • Laura Rieger

The main topics covered in their research encompass a variety of areas such as Privacy-Preserving Technologies in Data, Domain Adaptation and Few-Shot Learning, Topic Modeling, Explainable Artificial Intelligence (XAI), Machine Learning in Healthcare, Functional Brain Connectivity Studies, and EEG and Brain-Computer Interfaces.

Best Publications

  • Neural network ensembles

    L.K. Hansen;P. Salamon

  • Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook

    Magnus Nrgaard;O. E. Ravn;N. K. Poulsen;L. K. Hansen

  • Neural Networks for Modelling and Control of Dynamic Systems

    M. Nørgaard;O. Ravn;N. K. Poulsen;L. K. Hansen

  • Explainable ai – preface

    Wojciech Samek;Grégoire Montavon;Andrea Vedaldi;Lars Kai Hansen

  • On Clustering fMRI Time Series

    Cyril Goutte;Peter Aundal Toft;Egill Rostrup;Finn Årup Nielsen

  • Independent component analysis of functional MRI: what is signal and what is noise?

    Martin J McKeown;Lars Kai Hansen;Terrence J Sejnowsk;Terrence J Sejnowsk

  • Good Friends, Bad News - Affect and Virality in Twitter

    Lars Kai Hansen;Adam Arvidsson;Finn Aarup Nielsen;Elanor Colleoni

  • Melanoma Diagnosis by Raman Spectroscopy and Neural Networks: Structure Alterations in Proteins and Lipids in Intact Cancer Tissue

    Monika Gniadecka;Peter Alshede Philipsen;Sigurdur Sigurdsson;Sonja Wessel

  • Detection of skin cancer by classification of Raman spectra

    S. Sigurdsson;P.A. Philipsen;L.K. Hansen;J. Larsen

  • The quantitative evaluation of functional neuroimaging experiments: The NPAIRS data analysis framework

    Stephen C. Strother;Jon R. Anderson;Jon R. Anderson;Lars Kai Hansen;Ulrik Kjems

  • Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG.

    Morten Mørup;Lars Kai Hansen;Christoph S. Herrmann;Josef Parnas

  • Bayesian Non-negative Matrix Factorization

    Mikkel N. Schmidt;Ole Winther;Lars Kai Hansen

  • Archetypal analysis for machine learning and data mining

    Morten MøRup;Lars Kai Hansen

  • Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains.

    Ivana Konvalinka;Ivana Konvalinka;Markus Bauer;Carsten Stahlhut;Lars Kai Hansen

  • ICA of functional MRI data: an overview.

    Vince D. Calhoun;Tülay Adali;Lars Kai Hansen;Jan Larsen

  • Mining the posterior cingulate: segregation between memory and pain components.

    Finn Årup Nielsen;Daniela Balslev;Lars Kai Hansen

  • Generalizable patterns in neuroimaging: how many principal components?

    Lars Kai Hansen;Jan Larsen;Finn Årup Nielsen;Stephen C. Strother

  • Theorems on Positive Data: on the Uniqueness of NMF

    Hans Laurberg;Mads Græsbøll Christensen;Mark D. Plumbley;Lars Kai Hansen

  • Microstate EEGlab toolbox: An introductory guide

    Poulsen At;Pedroni A;Langer N;Hansen Lk

  • Mean-field approaches to independent component analysis

    Pedro A. D. F. R. Højen-Sørensen;Ole Winther;Lars Kai Hansen

  • Defining a local arterial input function for perfusion MRI using independent component analysis

    Fernando Calamante;Morten Mørup;Lars Kai Hansen

Frequent Co-Authors

Jan Larsen
Jan Larsen Technical University of Denmark
Stephen C. Strother
Stephen C. Strother University of Toronto
Ole Winther
Ole Winther Technical University of Denmark
Claus Svarer
Claus Svarer Copenhagen University Hospital
Nicholas Lange
Nicholas Lange Harvard University
Cyril Goutte
Cyril Goutte National Research Council Canada
John J. Sidtis
John J. Sidtis New York University
Carl Edward Rasmussen
Carl Edward Rasmussen University of Cambridge
Ian Law
Ian Law Copenhagen University Hospital
Niels Kjølstad Poulsen
Niels Kjølstad Poulsen Technical University of Denmark

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education in Computer Science opens the door to a variety of related fields and career opportunities. Choices aren’t limited to programming—students often branch out into technical areas like engineering, physics, or data science, each offering unique skillsets and job prospects.

Those curious about hardware, robotics, or manufacturing may benefit from learning about mechanical engineering degree cost, as affordability can be a deciding factor when choosing between disciplines. If you’re interested in theoretical concepts and foundational tech problems, you might consider a physics degree online.

For students aiming at high-growth tech sectors, pursuing the cheapest master in data science can provide specialized expertise in fields like artificial intelligence and big data. Alternatively, comparing programs using an online electrical engineering degree ranking helps you find highly-rated options with flexible study formats.

By considering related online degrees, students can expand their skills and take advantage of in-demand career pathways—all while balancing cost, flexibility, and future goals.

Best Scientists Citing Lars Kai Hansen

Trending Scientists