World's Best Scientists 2026 revealed!

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Computer Science

D-Index
33
Citations
6489
World Ranking
12481
National Ranking
794

Mathematics

D-Index
32
Citations
5119
World Ranking
3160
National Ranking
208

Overview

Dirk Husmeier is affiliated with the University of Glasgow in the United Kingdom. Their research primarily spans the field of Medicine, with a strong focus on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Biomedical Engineering, and Control and Systems Engineering.

The scientist's research topics include:

  • Cardiovascular Function and Risk Factors
  • Gaussian Processes and Bayesian Inference
  • Elasticity and Material Modeling
  • Probabilistic and Robust Engineering Design
  • Model Reduction and Neural Networks
  • Control Systems and Identification
  • Advanced MRI Techniques and Applications

Recent papers authored or co-authored by Dirk Husmeier are:

  • The Fully Convolutional Transformer for Medical Image Segmentation, 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • COVID-19 - exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study, 2020, Wellcome Open Research
  • COVID-19 - exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study, 2021, Wellcome Open Research
  • Rationale and design of the Medical Research Council's Precision Medicine with Zibotentan in Microvascular Angina (PRIZE) trial, 2020, American Heart Journal
  • Physics-informed graph neural network emulation of soft-tissue mechanics, 2023, Computer Methods in Applied Mechanics and Engineering

Co-authors frequently collaborating with Dirk Husmeier include:

  • Hao Gao
  • David R. Dalton
  • L. Mihaela Păun
  • Mette S. Olufsen
  • Colin Berry

The scientist has published extensively in the following venues:

  • Proceedings of the International Conference on Statistics, Theory and Applications (ICSTA...)
  • Wellcome Open Research
  • Computer Methods in Applied Mechanics and Engineering
  • arXiv (Cornell University)
  • SSRN Electronic Journal

Best Publications

  • TOPALi v2

    Iain Milne;Dominik Lindner;Micha Bayer;Dirk Husmeier

  • Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks.

    Dirk Husmeier

  • TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments

    Iain Milne;Frank Wright;Glenn Rowe;David F. Marshall

  • Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks

    Adriano V. Werhli;Marco Grzegorczyk;Dirk Husmeier

  • Bayesian approaches to Gaussian mixture modeling

    S.J. Roberts;D. Husmeier;I. Rezek;W. Penny

  • Reconstructing Gene Regulatory Networks with Bayesian Networks by Combining Expression Data with Multiple Sources of Prior Knowledge

    Adriano V Werhli;Dirk Husmeier

  • Probabilistic Modeling in Bioinformatics and Medical Informatics

    Dirk Husmeier;Richard Dybowski;Stephen Roberts

  • Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move

    Marco Grzegorczyk;Dirk Husmeier

  • COVID-19 - exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study

    Peter Hanlon;Fergus Chadwick;Anoop Shah;Rachael Wood

  • The Fully Convolutional Transformer for Medical Image Segmentation

    Unknown

  • ODE parameter inference using adaptive gradient matching with Gaussian processes

    Frank Dondelinger;Dirk Husmeier;Simon Rogers;Maurizio Filippone

  • Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure

    Frank Dondelinger;Sophie Lèbre;Dirk Husmeier

  • Improvements in the reconstruction of time-varying gene regulatory networks

    Marco Grzegorczyk;Dirk Husmeier

  • Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler

    Marco Grzegorczyk;Dirk Husmeier;Kieron D. Edwards;Peter Ghazal

  • Non-stationary continuous dynamic Bayesian networks

    Marco Grzegorczyk;Dirk Husmeier

  • Detecting Recombination in 4-Taxa DNA Sequence Alignments with Bayesian Hidden Markov Models and Markov Chain Monte Carlo

    Dirk Husmeier;Gráinne McGuire

  • Non-homogeneous dynamic Bayesian networks for continuous data

    Marco Grzegorczyk;Dirk Husmeier

  • Reverse engineering of genetic networks with Bayesian networks.

    D. Husmeier

  • Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods

    Ali Faisal;Frank Dondelinger;Dirk Husmeier;Colin M. Beale

  • GENE REGULATORY NETWORK RECONSTRUCTION BY BAYESIAN INTEGRATION OF PRIOR KNOWLEDGE AND/OR DIFFERENT EXPERIMENTAL CONDITIONS

    Adriano Velasque Werhli;Dirk Husmeier

  • Discussion on the paper by Handcock, Raftery and Tantrum

    Tom A. B. Snijders;Tony Robinson;Anthony C. Atkinson;Marco Riani

  • Clustering objects on subsets of attributes

    DJ Hand;C Glasbey;D Husmeier;JC Gower

Frequent Co-Authors

Colin Berry
Colin Berry University of Glasgow
Stephen J. Roberts
Stephen J. Roberts University of Oxford
William D. Penny
William D. Penny University of East Anglia
Robert H. Insall
Robert H. Insall University of Glasgow
Andrew J. Millar
Andrew J. Millar University of Edinburgh
Michael Fisher
Michael Fisher University of Manchester
Colin Fischbacher
Colin Fischbacher National Health Service Scotland
Peter Ghazal
Peter Ghazal Cardiff University
Kaspar Althoefer
Kaspar Althoefer Queen Mary University of London
David Marshall
David Marshall James Hutton Institute

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