Nikita Moriakov

Postdoctoral Researcher


Nikita Moriakov is a postdoctoral researcher working on developing novel AI methodologies for Oncology. Previously he obtained his Master's degree in Applied Mathematics from Delft University of Technology in 2012 (cum laude). In October 2016 he received his Ph.D. at the same university, defending thesis Entropy and Kolmogorov Complexity. He is currently working on the cancer risk prediction in breast imaging, and the reconstruction of cone-beam CT (CBCT) images in adaptive radiotherapy. His supervisors are Jonas Teuwen and Jan-Jakob Sonke.

  1. Y. Beauferris, J. Teuwen, D. Karkalousos, N. Moriakov, M. Caan, G. Yiasemis, L. Rodrigues, A. Lopes, H. Pedrini, L. Rittner, M. Dannecker, V. Studenyak, F. Gröger, D. Vyas, S. Faghih-Roohi, A. K. Jethi, J. C. Raju, M. Sivaprakasam, M. Lasby, N. Nogovitsyn, W. Loos, R. Frayne, R. Souza, "Multi-Coil MRI Reconstruction Challenge – Assessing Brain MRI Reconstruction Models and their Generalizability to Varying Coil Configurations", arXiv:2011.07952 [physics], 2021-12-21
  2. J. Teuwen, N. Moriakov, C. Fedon, M. Caballo, I. Reiser, P. Bakic, E. García, O. Diaz, K. Michielsen, I. Sechopoulos, "Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation", Medical Image Analysis, July 1, 2021, 71
  3. R. Sheombarsing, N. Moriakov, J. Sonke, J. Teuwen, "Subpixel object segmentation using wavelets and multi resolution analysis", arXiv:2110.15233 [cs, eess], 2021-10-28
  4. N. Moriakov, "Computable Følner monotilings and a theorem of Brudno", Ergodic Theory and Dynamical Systems, 2020
  5. N. Moriakov, A. Samudre, M. Negro, F. Gieseke, S. Otten, L. Hendriks, "Inferring astrophysical X-ray polarization with deep learning", arXiv:2005.08126 [astro-ph], 2020-05-16