• Tommi Heikkilä, Project Researcher (postdoc) in the LUT University, School of Engineering Sciences (Finland)
• Working on: applied math, inverse problems, sparse, nonlinear and/or dynamic tomography, wavelets and shearlets
• ORCID: 0000-0001-5505-8136
• LUT University Research portal

• WaveletLowRank: Wavelet Domain Local Low-Rank Algorithms
  Numerical validation of results in "MultiResolution Low-Rank Regularization of Dynamic Imaging Problems".

• randDynTomo: Statistical inverse learning of randomly sampled dynamic tomograhy
  Numerical validation of results in "Regularization with optimal space-time priors". Collaboration with T.A. Bubba and L. Ratti.

• 3d_cylind_shear: 3D Cylindrical shearlet transform for Matlab
  (Most of the work by G. Easley and D. Labate)

• dualtree4: 4D dual-tree complex wavelet transform for Matlab
  See also: "4D dual-tree complex wavelets for time-dependent data"

• wavedec4: 4D Discrete wavelet transform for Matlab

• 4dCylindricalShearlet: 4D Cylindrical shearlet transform for Matlab
  See also: "Efficient representation of spatio-temporal data using cylindrical shearlets"

• sliceViewerApp: Matlab app for viewing slices of 4D and 3D volumes
  

• T.H, H. Help & A. Meaney,
  Cone-beam Gel phantom data for dynamic X-ray tomography (2023). DOI:10.5281/zenodo.7739984
  

• T.H,
  STEMPO - dynamic X-ray tomography phantom (2022). DOI:10.5281/zenodo.7081688
  

• T.H, H. Help & A. Meaney,
  Gel phantom data for dynamic X-ray tomography (2020). DOI:10.5281/zenodo.3696816

1. T.A. Bubba, T.H, D. Labate & L. Ratti,
   Regularization with optimal space-time priors (2025).
   SIAM Journal on Imaging Sciences, 18(3), 1563-1600. DOI:10.1137/24M1661923 | arXiv:2405.06337 | pdf/ePrint

2. T.H,
   MultiResolution Low-Rank Regularization of Dynamic Imaging Problems (2025).
   Scale Space and Variational Methods in Computer Vision. SSVM 2025.
   Lecture Notes in Computer Science, vol 15667. Springer. DOI:10.1007/978-3-031-92366-1_6 | arXiv:2502.20977

3. J-B. Fest, T.H, I. Loris, S. Martin, L. Ratti, S: Rebegoldi & G. Sarnighausen,
   On a fixed point continuation method for a convex optimization problem (2022).
   Advanced Techniques in Optimization for Machine learning and Imaging (ATOMI), Springer INdAM Series, vol 61, p. 15-30. DOI:10.1007/978-981-97-6769-4_1 | arXiv:2212.12256

4. T.H,
   STEMPO - dynamic X-ray omography phantom (2022).
   Advanced Techniques in Optimization for Machine learning and Imaging (ATOMI), Springer INdAM Series, vol 61, p. 1-14. DOI:10.1007/978-981-97-6769-4_1 | arXiv:2209.12471

5. T.A. Bubba, G. Easley, T.H, D. Labate & J.P. Rodriguez Ayllon,
   Efficient representation of spatio-temporal data using cylindrical shearlets (2023).
   Journal of Computational and Applied Mathematics 429, 115206. DOI:10.1016/j.cam.2023.115206

6. T.A. Bubba, T.H & S. Siltanen,
   4D dual-tree complex wavelets for time-dependent data (2021).
   21st International Conference on Computational Science and Its Applications (ICCSA), IEEE, p. 146-156. DOI:10.1109/ICCSA54496.2021.00029

7. T.A. Bubba, T.H, H. Help, S. Huotari, Y. Salmon & S. Siltanen,
   Sparse dynamic tomography: Shearlet-based approach for iodine perfusion in plant stems (2020).
   Inverse Problems 36, 094002. DOI:10.1088/1361-6420/ab9c15

• Spatio-temporal regularization methods for sparse dynamic tomography (2024),
  PhD thesis, University of Helsinki, Finland. Dissertationes Universitatis Helsingiensis 60/2024.
  

Last edited: July 13, 2025