People
Professor
Sampsa Pursiainen
- Professor
- sovellettu matematiikka
- Faculty of Information Technology and Communication Sciences
- Tampere University
- +358407505677
- sampsa.pursiainen@tuni.fi
About me
My work has focused on the numerical mathematics of inverse problems since 2001. My dissertation completed in 2009 concerned numerical forward and inverse methods of biomedical imaging. Currently, my research concentrates on advancing the mathematical and computational methodology in the imaging applications of life and geosciences, where highly advanced technological applications often comprise incomplete data and scarce a priori information leading to ill-posed inverse problems. Characteristic to inverse imaging is that, in addition to the measurements, the quality of the results depends also on various other factors such as the applied measurement approach and mathematical methodology. Owing to the recent rapid increase in computational resources and the ability to handle massive amounts of data, the number of numerically approachable problems is growing constantly.
Since January 2019, I have served as an Associate Professor, Mathematics, Tampere University, where my goal is to continue and extend my ongoing international research cooperation. I am a team leader in the Finnish Centre of Excellence in Inverse Modelling and Imaging (2018-2025).
Associate Professor
Pasi Raumonen
- Associate Professor
- sovellettu matematiikka
- Faculty of Information Technology and Communication Sciences
- Tampere University
- +358503378719
- pasi.raumonen@tuni.fi
About me
I am an Associate Professor in applied mathematics and I have a background in electrical engineering. My current research concentrates on 3D structure modelling of trees and forests from laser scanner data, uncertainty quantification of such modelling, and their applications in forest and ecological research. I am also one of the Principal Investigators in Academy of Finland’s Centre of Excellence in Modelling and Imaging 2018-2025 and FAME – Flagship of Advanced Mathematics for Sensing, Imaging and Modelling (2024-).
Research topics
Applied mathematics, inverse problems, surface and object reconstruction, uncertainty quantification, tree and forest modelling, remote sensing (Lidar, point clouds)
Montagnoli A, Hudak A T, Raumonen P, Lasserre B, Terzaghi M, Silva C A, Bright B C, Vierling L A , de Vasconcellos B N, Chiatante D, Dumroese R K. 2024. Terrestrial laser scanning and low magnetic field digitization yield similar architectural coarse root traits for 32-year-old Pinus ponderosa trees. Plant Methods, 20, 102 (2024). https://doi.org/10.1186/s13007-024-01229-9
Su C, Kokosza A, Xie X, Pěnčík A, Zhang Y, Raumonen P, Shi X, Muranen S, Topcu M K, Immanen J, Hagqvist R, Safronov O, Alonso-Serra J, Eswaran G, Venegas M P, Ljung K, Ward S, Mähönen A, Himanen K, Salojärvi J, Fernie A R, Novák O, Leyser O, Pałubicki W, Helariutta Y, Nieminen K. 2023. Tree architecture: A strigolactone-deficient mutant reveals a connection between branching order and auxin gradient along the tree stem. Proceedings of the National Academy of Sciences of the United States of America, 2023 Vol. 120 No. 48 e2308587120, https://doi.org/10.1073/pnas.2308587120
Nunes M, Vaz M, Camargo J, Laurance W, de Andrade A, Vicentini A, Laurance S, Raumonen P, Jackson T, Zuquim G, Wu J, Penuelas J, ChaveJ, Maeda E. 2023, Edge effects on tree architecture exacerbate biomass loss of fragmented Amazonian forests. Nature Communications, 14, 8129 (2023). https://doi.org/10.1038/s41467-023-44004-5
Han T, Raumonen P, Sánchez-Azofeifa G A. 2023. A non-destructive approach to estimate buttress volume using 3D point cloud data. Ecological Informatics, Volume 77, November 2023, 102218. https://doi.org/10.1016/j.ecoinf.2023.102218
Calders K, Verbeeck H, Burt A, Origo N, Nightingale J, Malhi Y, Wilkes P, Raumonen P, Bunce R, Disney M. 2022. Laser scanning reveals potential underestimation of biomass carbon in temperate forest. Ecological Solutions and Evidence, 3, e12197. https://doi.org/10.1002/2688-8319.12197
Monica Herrero Huerta, Diego Gonzalez Aguilera, Pasi Raumonen. 2022. 4DRoot: root phenotyping software for temporal 3D scans by X-Ray Computed Tomography. Frontiers in Plant Science, Vol. 13, 2022, https://doi.org/10.3389/fpls.2022.986856
Brede B, Terryn L, Barbier N, Bartholomeu H Ms, Bartolo R, Calders K, Derroire G, Krishna Moorthy S, Lau A, Levick S R, Raumonen P,Verbeeck H, Wang D, Whiteside T, van der Zee J, Herold M. 2022. Non-destructive estimation of individual tree biomass: allometric models, terrestrial and UAV laser scanning. Remote Sensing of Environment, Vol 280, October 2022, 113180, https://doi.org/10.1016/j.rse.2022.113180
Maeda E, Nunes M, Calders K, Mendes de Moura Y, Raumonen P, Tuomisto H, Verley P, Vincent G, Zuquim G, Camargo J L. 2022. Shifts in structural diversity of Amazonian forest edges detected using terrestrial laser scanning. Remote Sensing of Environment, Vol 271, 15 March 2022, 112895, https://doi.org/10.1016/j.rse.2022.112895
Raumonen P, Brede B, Lau L, Bartholomeus H. 2021. A Shortest Path Based Tree Isolation Method For Uav Lidar Data. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 724-727,https://doi.org/10.1109/IGARSS47720.2021.9554346
Martin-Ducup O, II Mofack G, Wang D, Raumonen P, Ploton P, Sonké B, Barbier N, Couteron P, Pélissier R. 2021. Evaluation of automated pipelines for tree and plot metric estimation from TLS data in tropical forest areas. Annals of Botany, mcab051, https://doi.org/10.1093/aob/mcab051
Beyer R M, Basler D, Raumonen P, Kaasalainen M, Pretzsch H. 2021. Do trees have constant branch divergence angles? Journal of Theoretical Biology, Volume 512, 7 March 2021, 110567, https://doi.org/10.1016/j.jtbi.2020.110567
He, H.; Chen, X.; Mehmood, A.; Raivio, L.; Huttunen, H.; Raumonen, P.; Virkki, J. 2020. ClothFace: A Batteryless RFID-Based Textile Platform for Handwriting Recognition. Sensors, 2020, 20, 4878. https://doi.org/10.3390/s20174878
Terryn L, Calders K, Disney M, Origo N, Malhi Y, Newnham G, Raumonen P, Åkerblom M, Verbeeck M. 2020. Tree species classification using structural features derived from terrestrial laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 168, October 2020, pp. 170–181. https://doi.org/10.1016/j.isprsjprs.2020.08.009
Krishna Moorthy S M, Raumonen P, den Bulcke J V, Calders K, Verbeeck H. 2020. Terrestrial laser scanning for non-destructive estimates of liana stem biomass. Forest Ecology and Management, Volume 456, 15 January 2020, 117751, 14p, https://doi.org/10.1016/j.foreco.2019.117751
Kunz M, Fichtner A, Härdtle W, Raumonen P, Bruelheide H, von Oheimb G. 2019. Neighbour species richness and local structural variability modulate aboveground allocation patterns and crown morphology of individual trees. Ecology Letters, Volume 22, Issue 12, December 2019, pp. 2130-2140, https://doi.org/10.1111/ele.13400
Brede B, Calders K, Lau A, Raumonen P, Bartholomeus H M, Herold M, Kooistra L. 2019. Non-destructive Tree Volume Estimation through Quantitative Structure Modelling: Comparing UAV Laser Scanning with Terrestrial Lidar. Remote Sensing of Environment, Volume 233, November 2019, 111355, https://doi.org/10.1016/j.rse.2019.111355
Pitkänen T, Raumonen P, Kangas A. 2019. Measuring stem diameters with TLS in boreal forests by complementary fitting procedure. ISPRS Journal of Photogrammetry and Remote Sensing, Volume 147, January 2019, Pages 294-306, https://doi.org/10.1016/j.isprsjprs.2018.11.027
Jackson T, Shenkin A, Wellpott A, Calders K, Origo N, Disney M, Burt A, Raumonen P, Gardiner B, Herold M, Fourcaud T, Malhi Y. 2019. Finite element analysis of trees in the wind based on terrestrial laser scanning data. Agricultural and Forest Meteorology, Volume 265, 2019, Pages 137-144. https://doi.org/10.1016/j.agrformet.2018.11.014
Raumonen P, Tarvainen T. 2018. Segmentation of vessel structures from photoacoustic images with reliability assessment. Biomedical Optics Express, Vol. 9, Issue 7, pp. 2887-2904, https://doi.org/10.1364/BOE.9.002887
Sievänen R, Raumonen P, Perttunen J, Nikinmaa E, Kaitaniemi P. 2018. A study of crown development mechanisms using a shoot-based tree model and segmented terrestrial laser scanning data. Annals of Botany, Volume 122, Issue 3, 27 August 2018, Pages 423–434, https://doi.org/10.1093/aob/mcy082
Disney M, Boni Vicari M, Burt A, Calders K, Lewis S, Raumonen P, Wilkes P. 2018. Weighing trees with lasers: advances, challenges and opportunities. Interface Focus 8: 20170048. http://dx.doi.org/10.1098/rsfs.2017.0048
Gonzalez de Tanago Menaca J, Lau A, Bartholomeus H, Herold M, Avitabile V, Raumonen P, Martius C, Goodman R, Disney M, Manuri S, Burt A, Calders K. 2018. Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR. Methods in Ecology and Evolution, Vol. 9, Issue 2, pp. 223-234, https://doi.org/10.1111/2041-210X.12904
Åkerblom M, Raumonen P, Mäkipää R, Kaasalainen M. 2017. Automatic tree species recognition with quantitative structure models. Remote Sensing of Environment, Vol. 191, 1-12, https://doi.org/10.1016/j.rse.2016.12.002
Potapov I, Järvenpää M, Åkerblom M, Raumonen P, Kaasalainen M. 2017. Bayes Forest: a data-intensive generator of morphological tree clones. GigaScience, Vol. 6, Issue 10, Pages 1–13, gix079, https://doi.org/10.1093/gigascience/gix079
Hackenberg J, Spiecker H, Calders K, Disney M, Raumonen P. 2015. SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds. Forests, Vol. 6, No. 11, 4245-4294, https://doi.org/10.3390/f6114245
Calders K, Newnham G, Burt A, Murphy S, Raumonen P, Herold M, Culvenor D, Avitabile V, Disney M, Armston J, Kaasalainen M. 2015. Non-destructive estimates of above-ground biomass using terrestrial laser scanning. Methods in Ecology and Evolution, Vol. 6, No. 2, pp. 198-208, https://doi.org/10.1111/2041-210X.12301
Raumonen P, Casella E, Calders K, Murphy S, Åkerblom M, Kaasalainen M. 2015. Massive-scale Tree Modelling from TLS Data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-3/W4, 189-196. https://doi.org/10.5194/isprsannals-II-3-W4-189-2015
Smith A, Astrup R, Raumonen P, Liski J, Krooks A, Kaasalainen S, Åkerblom M, Kaasalainen M. 2014. Tree Root system characterization and volume estimation by terrestrial laser scanning. Forests, Vol. 5, No. 12, pp. 3274-3294, https://doi.org/10.3390/f5123274
Janka M, Saukko E, Raumonen P, Lupo D. 2014. Optimization of large-area OLED current distribution grids with self-aligned passivation. Organic Electronics, Vol. 15, No. 12, pp. 3431–3438, https://doi.org/10.1016/j.orgel.2014.09.028
Raumonen P, Kaasalainen M, Åkerblom M, Kaasalainen S, Kaartinen H, Vastaranta M, Holopainen M, Disney M, Lewis P. 2013. Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data. Remote Sensing, Vol. 5, No. 2, pp. 491-520, https://doi.org/10.3390/rs5020491
Stenvall A, Tarhasaari T, Grilli F, Raumonen P, Vojenciak M, Pellikka M. 2012 Manifolds in electromagnetism and superconductor modelling: using their properties to model critical current of twisted conductors in self-field with 2-D model. Cryogenics, Vol. 53, Special issue SI, pp. 135–141, https://doi.org/10.1016/j.cryogenics.2012.06.005
Raumonen P, Suuriniemi S, Kettunen L. 2011. Dimensional Reduction of Electromagnetic Boundary Value Problems. Boundary Value Problems 2011, 2011:9, https://doi.org/10.1186/1687-2770-2011-9
Calvano F, Raumonen P, Suuriniemi S, Kettunen L, Rubinacci G. 2010. Size Is in the Eye of the Beholder: Technique for Non-destructive Detection of Parameterized Defects. IEEE Transaction on Magnetics, Vol. 46, No. 8, pp. 3006-3009. DOI: 10.1109/TMAG.2010.2044564
Raumonen P, Suuriniemi S, Kettunen L. 2008. Applications of manifolds: mesh generation. IET Science, Measurement & Technology, Vol. 2, No. 5, pp. 286-294. DOI: 10.1049/iet-smt:20070101
Raumonen P, Sydänheimo L, Ukkonen L, Keskilammi M, Kivikoski M. 2003. Folded dipole antenna near metal plate. Proc. of Antennas and Propagation Society International Symposium, 22.-27.7. 2003. IEEE, Vol. 1, pp. 848-851. DOI: 10.1109/APS.2003.1217593
Post Docs
Alexandra Koulouri
- Postdoctoral Research Fellow
- Faculty of Information Technology and Communication Sciences
- Tampere University
- alexandra.koulouri@tuni.fi
About me
I hold a PhD degree in EEG Brain Imaging and Tomographic Imaging from Imperial College London, Dept. of Electrical and Electronic Engineering, UK.
I am interested in new collaborations!
I really enjoy diving into new topics or expanding my horizons in topics related to neuroimaging, microscopy and climate or weather forecasting.
Please contact me either at alexandra.koulouri@tuni.fi or my personal email a.koulouri84@gmail.com
Responsibilities
Currently, I am a post-doctoral Academy researcher.
My research work is titled ''Superresolution in inverse problems with applications in NeuroImaging and Fluoresent Microscopy''.
I am interested in problems related to remote sensing, extraction information using limited data, real time tracking, data assimilation and forecasting (e.g. using Kalman and Bayesian filtering), convex/non-convex optimization algorithms using sparsity constraints, adaptive mesh approaches and uncertainty modelling in inverse problems.
The applications I am involved at the moment, are related to
- (focal) brain source imaging using non-invasive EEG recording
- estimation of the skull conductivity and brain activity combining EEG and Electrical Impedance Tomography
- detection and visualization of single molecules in fluoresence microscopy, tracking of particles in microscopy
- dynamic imaging (an intereting application that I tried recently using my knowledge: imaging ionospheric S4 scintillation for GNSS users).
Field of expertise
My expertise is in Bayesian inverse problems, optimization techniques, tomographic methods, imaging processing, super-resolution algorithms and machine learning approaches.
Research career
Currently: Academy PostDoc Researcher
Previously:
• Researcher in the Ionospheric imaging group, EEE Dept., University of Bath, May 2018- Oct. 2018
• Research fellow in the group of Bioelectromagentism, School of Physics, Aristotle University of Thessaloniki, Greece, Nov. 2016 – Oct. 2017
• Teacher in the Master Programme of Bioinformatics and Neuroinformatics, Ionian University, Dept. of Informatics, 7 Pl. Tsirigoti, 49100, Greece, Oct. 2016 – Jan. 2017
• Researcher, 1 Oct. 2014 – 31 July 2016, Imaging group, Institute for Computational and Applied Mathematics, University of Münster. Collaboration with the reproductive clinic of the University of Münster (super-resolution imaging strategies in Raman spectroscopy for DNA detection anomalies)
• PhD researcher, 2010 – 2014, Comm. And Sig. Proc. group, EEE department, Imperial College London, PhD studies and research on algorithms in electrical brain imaging
Academy of Finland, Post-doc research project, 2018-2021 (project brief description)
ATTRACT consortium, EC Horizon 2014-2020, 2019 – 2020 (project temporary webpage)
IKY Fellowship of excellence for postgraduate studies in Greece - Siemens program, 2016-2017
PhD grant by John S. Latsis Public Benefit Foundation, 2010-2013 (3 years)
Studentship EPSRC, UCL, 2008-2009
Studentship by John S. Latsis Public Benefit Foundation, 2008-2009
Participate in HYPERMATH project (2014-2016) funded by German BMBF for the development super-resolution algorithms in microscopy and Raman spectroscopy in Muenster University
• A. Koulouri, P. Heins and M. Burger, Adaptive Superresolution in Deconvolution of Sparse Peaks, in IEEE Transactions on Signal Processing, vol. 69, pp. 165-178, 2021, doi: 10.1109/TSP.2020.3037373. (Matlab Codes)
• V. Rimpiläinen, T. Samaras, A. Koulouri, Electrical Impedance Tomography with Box Constraint for Skull Conductivity Estimation. EMBEC 2020. IFMBE Proceedings, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-64610-3_54 (arXiv:2001.11830)
• A. Koulouri, V. Rimpiläinen, Simultaneous Skull Conductivity and Focal Source Imaging from EEG Recordings with the Help of Bayesian Uncertainty Modelling. EMBEC 2020. IFMBE Proceedings, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-64610-3_114 (arXiv:2002.00066), Finalist in the Young Investigator Competition
• A. Rezaei, A. Koulouri & S. Pursiainen Randomized Multiresolution Scanning in Focal and Fast E/MEG Sensing of Brain Activity with a Variable Depth. Brain Topogr 33, 161–175 (2020). https://doi.org/10.1007/s10548-020-00755-8
• A. Koulouri, N. Smith, B. Vani, V. Rimpiläinen, A. Astin and B. Forte Methodology to estimate ionospheric scintillation risk maps and their contribution to position dilution of precision on the ground, J Geod 94, 22 (2020). https://doi.org/10.1007/s00190-020-01344-0 (Matlab Codes)
•A. Koulouri, V. Rimpiläinen and N. Smith, Position Dilution of Precision and Bayesian Model of the Observation Error (2020arXiv:2001.02198)
• V. Rimpiläinen, A. Koulouri, F. Lucka, J.P. Kaipio, C.H. Wolters, Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity, NeuroImage, 188, 252-256, 2019. https://doi.org/10.1016/j.neuroimage.2018.11.058
• A. Koulouri, V. Rimpiläinen, M. Brookes. J.P. Kaipio, Prior Variances and Depth Un-biased Estimators in EEG Focal source Imaging, EMBEC & NBC 2017, International Federation for Medical and Biological Engineering (IFMBE) Proceedings, 65, 33-36, 2017 (arXiv version :1703.09044)
• V. Rimpiläinen, A. Koulouri, F. Lucka, J.P. Kaipio, C.H. Wolters, Bayesian Modelling of Skull Conductivity Uncertainties in EEG Source Imaging, EMBEC & NBC 2017, International Federation for Medical and Biological Engineering (IFMBE) Proceedings, 65, 892-895, 2017 (arXiv:1703.0903 )
• A. Koulouri, M. Brookes and V. Rimpilainen. Vector tomography for reconstructing electric field with non-zero divergence in bounded domains, Journal of Computational Physic ,Vol. 329, 15 January 2017, Pages 73–90. https://doi.org/10.1016/j.jcp.2016.10.037
• A. Koulouri, V. Rimpilainen, M. Brookes and J. P. Kaipio. Compensation of domain modelling errors in the inverse source problem of the Poisson equation: application in electroencephalographic imaging, Applied Numerical Mathematics, Vol. 106, Aug. 2016, P. 24-36. https://doi.org/10.1016/j.apnum.2016.01.005
• A. Koulouri and M. Petrou: Vector Field Tomography: Reconstruction of an Irrotational Field in the Discrete Domain, Proceeding (778) Signal Processing, Pattern Recognition and Applications, 2012, DOI: 10.2316/P.2012.778-021
• Automatic segmentation of the abdominal Aorta from CT images: an initial approach towards the aortic Aneurysm detection. Authors: Alexandra Koulouri, Prof. Maria Petrou. Publisher: LAP LAMBERT Academic Publishing (22 May 2011).
Older thesis in CT segmentation:
Automatic segmentation of the thoracic organs for image registration and RT planning, UCL, October 2009, doi: 10.13140/RG.2.1.3136.1526
Automatic Segmentation and 3D Reconstruction of the Abdominal Aorta from CT images, Imperial College, September 2008: full text
Maryamolsadat Samavaki
- Postdoctoral Research Fellow
- Faculty of Information Technology and Communication Sciences
- Tampere University
- +358505213308
- maryamolsadat.samavaki@tuni.fi
Doctoral Researchers
Joonas Lahtinen
- Part-Time Teacher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- joonas.j.lahtinen@tuni.fi
Research topics
Source localization from non-invasive brain imaging data
Research fields
Inversion problems
Conditionally Exponential Prior in Focal Near- and Far-Field EEG Source Localization via Randomized Multiresolution Scanning (RAMUS):
https://arxiv.org/abs/2106.03489
Oluwatoki Yusuf
- Doctoral Researcher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- +358504730993
- yusuf.yusuf@tuni.fi
Research topics
FETD-Based Tomographic Full-Wave Radar Imaging of Small Solar System Body Interiors
Research unit
Computing Sciences
Vincent Verhoeven
- Doctoral Researcher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- vincentius.verhoeven@tuni.fi
About me
PhD candidate quantifying the uncertainty of tree reconstruction with laser data.
Member of the inverse problems group (https://research.tuni.fi/inverse/).
Research fields
- Remote sensing
- Laser scanning
- Uncertainty quantification
- Geometrical reconstruction
Santtu Söderholm
- Doctoral Researcher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- +358504089805
- santtu.soderholm@tuni.fi
Responsibilities
Development of Zeffiro Interface and other tasks related to the work of a doctoral researcher.
Modeling of blood flow in cerebral arterial circulation and its dynamic impact on electrical conductivity in a realistic multi-compartment head model
Samavaki, M., Söderholm, S., Nia, A. Z. & Pursiainen, S., helmik. 2024, julkaisussa: Computer Methods and Programs in Biomedicine. 244, 107983.Tutkimustuotos: Artikkeli › Scientific › vertaisarvioitu
The effects of peeling on finite element method-based EEG source reconstruction
Söderholm, S., Lahtinen, J., Wolters, C. H. & Pursiainen, S., maalisk. 2024, julkaisussa: Biomedical Signal Prosessing And Control. 89, 14 Sivumäärä, 105695.Tutkimustuotos: Artikkeli › Scientific › vertaisarvioitu
Pressure–Poisson equation in numerical simulation of cerebral arterial circulation and its effect on the electrical conductivity of the brain
Samavaki, M., Oluwatoki Yusuf, Y., Nia, A. Z., Söderholm, S., Lahtinen, J., Galaz Prieto, F. & Pursiainen, S., jouluk. 2023, julkaisussa: Computer Methods and Programs in Biomedicine. 242, 107844.Tutkimustuotos: Artikkeli › Scientific › vertaisarvioitu
Pietari Mönkkönen
- Doctoral Researcher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- pietari.monkkonen@tuni.fi
Pranjali Singh
- Doctoral Researcher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- pranjali.singh@tuni.fi
Ishan Sen
- Doctoral Researcher
- Faculty of Information Technology and Communication Sciences
- Tampere University
- +358504076047
- ishan.sen@tuni.fi
About me
I am a doctoral researcher and my research focuses on Artificial Intelligence, Machine Learning, and Signal Processing. Currently, I am working on the development of advanced Augmentation and Alternative Communication (AAC) systems. The objectives are that the systems should be more situation-aware and capable of learning user’s habits, which could provide a better way for communicating for the user with a cognitive or speaking disability.