Zenith Purisha, S.Si., M.Sc., Ph.D.

Biography

Zenith Purisha received the undergraduate and master degrees in Mathematics from Universitas Gadjah Mada, Indonesia, in 2008 and 2011, respectively. In 2018, she received Ph.D degree in Mathematics from University of Helsinki, Finland. She did a postdoctoral program from 2018 to 2020 in Department of Electrical Engineering and Automation (EEA), Aalto University, Finland. Currently, she is a lecturer in Mathematics Department, Faculty of Science at Universitas Gadjah Mada, Indonesia. She is a member of Computational Mathematics research group.

Her expertise is in the field of computational inverse problems with an application to tomographic reconstruction using real data.

Research interests

Zenith’s research is x-ray tomographic reconstruction using computational inversion methods from under-sampled data. Her initial research interest was tomographic inversion using NURBS (Non-Uniform Rational B-Splines) and Markov chain Monte Carlo (MCMC). Present focus is on iterative inversion methods using Gaussian processes and sparsity promoting regularization such as wavelet and shearlets. Her interest also includes dynamic x-ray tomography reconstruction using Kalman filter.

Students

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Publications:

1. Brücken, E., Bharthuar, S., Emzir, M., Golovleva, M., Gädda, A., Hostettler, R., Härkönen, J., Kirschenmann, S., Litichevskyi, V., Luukka, P. and Martikainen, L., Naaranoja, T., Nincă, I., Ott, J., Petrow, H., Purisha, P., Siiskonen, T., Särkkä, S., Tikkanen, J., Tuuva, T. and Winkler, A., 2020. Multispectral photon-counting for medical imaging and beam characterization. Journal of Instrumentation, 15(02), p.C02024.
2. Purisha, Z., Jidling, C., Wahlström, N., Schön, T.B. and Särkkä, S., 2019. Probabilistic approach to limited-data computed tomography reconstruction. Inverse Problems, 35(10), p.105004.
3. Leino, M.K., Ala-Laurinaho, J., Purisha, Z., Särkkä, S. and Viikari, V., 2019, May. Millimeter-wave imaging method based on frequency-diverse subarrays. In 2019 12th Global Symposium on Millimeter Waves (GSMM) (pp. 84-86). IEEE.
4. Hakkarainen, J., Purisha, Z., Solonen, A. and Siltanen, S., 2019. Undersampled dynamic X-ray tomography with dimension reduction Kalman filter. IEEE Transactions on Computational Imaging, 5(3), pp.492-501.
5. Purisha, Z., Karhula, S.S., Ketola, J.H., Rimpeläinen, J., Nieminen, M.T., Saarakkala, S., Kröger, H. and Siltanen, S., 2018. An automatic regularization method: An application for 3-D X-ray micro-CT reconstruction using sparse data. IEEE transactions on medical imaging, 38(2), pp.417-425.
6. Purisha, Z., Rimpeläinen, J., Bubba, T. and Siltanen, S., 2017. Controlled wavelet domain sparsity for x-ray tomography. Measurement Science and Technology, 29(1), p.014002.
7. Haario, H., Kallonen, A., Laine, M., Niemi, E., Purisha, Z. and Siltanen, S., 2017. Shape recovery for sparse‐data tomography. Mathematical Methods in the Applied Sciences, 40(18), pp.6649-6669.
8. Bubba, T.A., März, M., Purisha, Z., Lassas, M. and Siltanen, S., 2017, August. Shearlet-based regularization in sparse dynamic tomography. In Wavelets and Sparsity XVII (Vol. 10394, pp. 236-245). SPIE.
9. Purisha, Z. and Siltanen, S., 2016. Tomographic Inversion using NURBS and MCMC. In Forging Connections between Computational Mathematics and Computational Geometry (pp. 153-166). Springer, Cham.
10. Purisha, Z. and Siltanen, S., 2013, September. Tomographic reconstruction of homogeneous 2d geometric models with unknown attenuation. In IFIP Conference on System Modeling and Optimization (pp. 247-256). Springer, Berlin, Heidelberg.