Dr Yury Korolev


  • Apr 2018 - date: Newton International Fellow, University of Cambridge
  • Oct 2017 - Mar 2018: Humboldt Fellow, University of Muenster
  • Jan 2017 - Sep 2017: Postdoc, University of Luebeck
  • Jan 2014 - Dec 2016: Postdoc, Queen Mary University of London
  • Mar 2013 - Dec 2013: Instructor, Moscow State University
  • Mar 2010 - Mar 2013: PhD student, Moscow State University


Yury is a Newton International Fellow at the Department of Applied Mathematics and Theoretical Physics and a member of the Cambridge Image Analysis group. He is also a Fellow of Hughes Hall, University of Cambridge. Yury is interested in inverse problems, variational regularisation and imaging science. Broadly speaking, inverse problems deal with extracting information from indirectly measured data using models that describe the data acquisition and arise, for instance, in medical imaging, astronomy, microscopy and geoscience. Yury develops robust approaches that can take into account the imperfect nature of the available mathematical models of real-world phenomena while keeping the computational complexity at a reasonable level.


I am teaching Inverse Problems in Imaging in Michaelmas term 2018/19.


2018 Research Fellowship of Hughes Hall, University of Cambridge (3 years)
2017 Newton International Fellowship (2 years)
2017 Humboldt Research Fellowship for Postdoctoral Researchers (2 years)
2009 Tikhonov scholarship for excellent academic and research results (1 year)
2007 Potanin scholarship for excellent academic results and leadership skills (1 year)


Peer reviewed journals:

  • M. Burger, Y. Korolev, J. Rasch (2018). Convergence rates and structure of solutions of inverse problems with imperfect forward models // submitted. arXiv:1806.10038
  • Y. Korolev, J. Lellmann (2018). Image reconstruction with imperfect forward models and applications in deblurring // SIAM Journal on Imaging Sciences, 11(1), 197-218
  • A. Gorokh, Y. Korolev, T. Valkonen (2016). Diffusion tensor imaging with deterministic error bounds // Journal of Mathematical Imaging and Vision, 56(1), 137-157
  • Y. Korolev (2014). Making use of partial order in solving inverse problems: II // Inverse Problems, 30(8), 085003
  • Y. Korolev, A. Yagola (2013). Making use of partial order in solving inverse problems // Inverse Problems, 29(9), 095012
  • Y. Korolev, A. Yagola (2012). On inverse problems in partially ordered spaces with a priori information // Journal of Inverse and Ill-posed Problems, 20(4), pp. 567-573
  • Y. Korolev, H. Kubo, A. Yagola (2012). Parameter identification problem for a parabolic equation – application to the Black–Scholes option pricing model // Journal of Inverse and Ill-posed Problems, 20(3), pp. 327-337
  • Y. Korolev, A. Yagola (2012). Error estimation in linear ill-posed problems with prior information // Computational methods and programming, vol. 13, pp. 14-18 (in Russian)
  • Y. Korolev, P. Golubtsov (2010). Two-level competition systems in common resource management problems // Mathematical game theory and applications, 2(4), pp. 25-51 (in Russian)

Conference proceedings:

  • Y. Korolev, V. Toropov, S. Shahpar (2017). Design Optimization Under Uncertainty Using the Multipoint Approximation Method // Proceedings of the 19th AIAA Non-Deterministic Approaches Conference, Grapevine TX, USA
  • Y. Korolev, V. Toropov, S. Shahpar (2015). Large-scale CFD Optimisation based on the FFD Parametrisation using the Multipoint Approximation Method in an HPC Environment // Proceedings of the 16th AIAA/ISSMO Multidisciplinary Analysis and Optimisation Conference, Dallas TX, USA
  • Y. Korolev, S. Karabasov, V. Toropov (2015). Automatic Optimizer vs Human Optimizer for Low-Order Jet Noise Modelling // Proceedings of the 21st AIAA/CEAS Aeroacoustics Conference, Dallas TX, USA
  • Y. Korolev, V. Toropov (2015). The Multipoint Approximation Method as a parallel optimisation framework for problems with computationally expensive responses // Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering, Dubrovnik, Croatia
  • Y. Korolev, A. Yagola, J. Johnson, D. Brinkerhoff (2013). Methods of error estimation in inverse problems on compact sets in Banach lattices – theory and applications in ice sheet modeling // Proceedings of the 4th Inverse Problems, Design and Optimisation symposium, Albi, France
  • A. Yagola, Y. Korolev (2012). Error estimations in linear inverse problems in ordered spaces // Proceedings of the 8th Congress of the International Society for Analysis, its Applications, and Computations, vol. 2. Peoples’ Friendship University of Russia, Moscow, p. 60–68
  • A. Yagola, Y. Korolev (2011). Error estimations in linear inverse problems with a priori information // Proceedings of the ASME 2011 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE, Washington DC, USA, DETC2011-47799
  • Y. Korolev, P. Golubtsov (2009). Modelling of common resource management problems // Proceedings of the “Lomonosov readings” conference, Moscow, Russia (in Russian)

Book chapter:

  • A. G. Yagola and Y. M. Korolev (2013). Error estimation in ill-posed problems in special cases // Applied Inverse Problems. Vol. 48 of Springer Proceedings in Mathematics & Statistics. Springer, New York, p. 155–164