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Mathematics

D-Index
44
Citations
13235
World Ranking
1539
National Ranking
663

Engineering and Technology

D-Index
44
Citations
13460
World Ranking
5682
National Ranking
1584

Overview

Erkki Somersalo is affiliated with Case Western Reserve University in the United States. Their research spans multiple fields, primarily focusing on engineering and computer science, with significant contributions to subfields such as artificial intelligence, computational mechanics, biomedical engineering, cognitive neuroscience, and modeling and simulation.

Their work covers various topics including sparse and compressive sensing techniques, COVID-19 epidemiological studies, Gaussian processes and Bayesian inference, numerical methods in inverse problems, electrical and bioimpedance tomography, SARS-CoV-2 and COVID-19 research, and blind source separation techniques.

Erkki Somersalo has coauthored extensively with several researchers, notably Daniela Calvetti, Monica Pragliola, Alexander Hoover, Johnie Rose, and Alberto Bocchinfuso.

Frequent publication venues for their research include arXiv (Cornell University), Inverse Problems, SSRN Electronic Journal, SIAM Journal on Scientific Computing, and Inverse Problems and Imaging.

Recent papers authored or coauthored by Somersalo include:

  • Sparsity promoting hybrid solvers for hierarchical bayesian inverse problems, 2020, Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)
  • Bayesian particle filter algorithm for learning epidemic dynamics, 2021, Inverse Problems
  • Bayesian dynamical estimation of the parameters of an SE(A)IR COVID-19 spread model, 2020, arXiv (Cornell University)
  • Computationally Efficient Sampling Methods for Sparsity Promoting Hierarchical Bayesian Models, 2024, SIAM/ASA Journal on Uncertainty Quantification
  • Metapopulation Network Models for Understanding, Predicting, and Managing the Coronavirus Disease COVID-19, 2020, Frontiers in Physics

Somersalo has contributed to book publications from notable publishers, including:

  • Society for Industrial and Applied Mathematics:
    • Mathematics of Data Science: A Computational Approach to Clustering and Classification, 2020
    • The Less Is More Linear Algebra of Vector Spaces and Matrices, 2022
  • Springer Nature:
    • Bayesian Scientific Computing, 2023

Best Publications

  • Statistical and computational inverse problems

    Jari Kaipio;Erkki Somersalo

  • Existence and uniqueness for electrode models for electric current computed tomography

    Erkki Somersalo;Margaret Cheney;David Isaacson

  • Tikhonov regularization and prior information in electrical impedance tomography

    M. Vauhkonen;D. Vadasz;P.A. Karjalainen;E. Somersalo

  • Visualization of magnetoencephalographic data using minimum current estimates.

    K. Uutela;M. Hämäläinen;E. Somersalo

  • Statistical inverse problems: discretization, model reduction and inverse crimes

    Jari Kaipio;Erkki Somersalo

  • Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography

    Jari P Kaipio;Ville Kolehmainen;Erkki Somersalo;Marko Vauhkonen

  • Inverse problems with structural prior information

    J P Kaipio;V Kolehmainen;M Vauhkonen;E Somersalo

  • Approximation errors and model reduction with an application in optical diffusion tomography

    S R Arridge;J P Kaipio;V Kolehmainen;M Schweiger

  • An inverse boundary value problem in electrodynamics

    Petri Ola;Lassi Päivärinta;Erkki Somersalo

  • Introduction to Bayesian Scientific Computing: Ten Lectures on Subjective Computing

    Daniela Calvetti;Erkki Somersalo

  • On the existence and convergence of the solution of PML equations

    Matti Lassas;Erkki Somersalo

  • Statistical inversion for medical x-ray tomography with few radiographs: I. General theory

    S Siltanen;V Kolehmainen;S Järvenpää;J P Kaipio

  • Layer stripping: a direct numerical method for impedance imaging

    E Somersalo;M Cheney;D Isaacson;E Isaacson

  • Anisotropic effects in highly scattering media

    Jenni Heino;Simon Arridge;Jan Sikora;Erkki Somersalo

  • Electromagnetic inverse problems and generalized Sommerfeld potentials

    Petri Ola;Erkki Somersalo

  • State estimation with fluid dynamical evolution models in process tomography - an application to impedance tomography

    A Seppänen;M Vauhkonen;P J Vauhkonen;E Somersalo

  • Statistical inversion for medical x-ray tomography with few radiographs: II. Application to dental radiology.

    V. Kolehmainen;S. Siltanen;Seppo Järvenpää;J. Kaipio

  • Hypermodels in the Bayesian imaging framework

    Daniela Calvetti;Erkki Somersalo

  • Inverse problems: From regularization to Bayesian inference

    D. Calvetti;E. Somersalo

  • Electrical impedance tomography with basis constraints

    M. Vauhkonen;J.P. Kaipio;E. Somersalo;P.A. Karjalainen

  • Introduction to Bayesian Scientific Computing: Ten Lectures on Subjective Computing (Surveys and Tutorials in the Applied Mathematical Sciences)

    Daniela Calvetti;Erkki Somersalo

Frequent Co-Authors

Daniela Calvetti
Daniela Calvetti Case Western Reserve University
Jari P. Kaipio
Jari P. Kaipio University of Auckland
Marko Vauhkonen
Marko Vauhkonen University of Eastern Finland
Matti Lassas
Matti Lassas University of Helsinki
David Isaacson
David Isaacson Rensselaer Polytechnic Institute
Ville Kolehmainen
Ville Kolehmainen University of Eastern Finland
Martti Hallikainen
Martti Hallikainen Aalto University
Simon R. Arridge
Simon R. Arridge University College London
Juha Hyyppä
Juha Hyyppä Finnish Geospatial Research Institute
Marco Viceconti
Marco Viceconti University of Bologna

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