My name is Svetlana Dubinkina, and I am a mathematician

Earth sciences provide with an endless source of fascinating problems related to weather, climate, subsurface structure of the Earth, to name a few. A question that could be posed is, “Are the changes predictable?” Because then we could stop (reverse) the climate change, predict how much wind energy we are going to produce next 10 years, how much oil or gas is still below the surface and where it is located. To answer these questions requires an interdisciplinary collaboration between scientists from mathematics, physics, climatology, geology, and engineering.

“Alone we can do so little; together we can do so much” ― Helen Keller

Photo Credit: Victor Lacken


I am an assistant professor at the VU Amsterdam. My research interests include numerical methods, statistical mechanics, data assimilation, paleoclimate, subsurface flow, wind energy, pipe flow.

    Ultimate goals of running projects are
  • ― to develop a novel data assimilation method that could tackle the problem of predicting climatological evens such as Little Ice Age that happened roughly 1400–1700 AD and a switch between two paths of Kuroshio current that happens abruptly and has a significant influence on local economics;
  • ― to predict the evolution of subsurface flows given a few local observations from wells and as a consequence to predict production rates of gas;
  • ― to predict formation of slugs in the pipes and their propagation, since those can cause unstable, intermittent production which can even kill a producing well;
  • ― to predict severe magnetic storms a few hours in advance in order to put a satellite in a sleeping mode such that the satellite would not be destroyed.

Acquired funds

  • ― the Lorentz Center, NDNS+ cluster, STAR cluster for organizing a Lorentz Center workshop (PI), 2016
  • ― Shell-NWO/FOM program (PI), 2015, Ph.D. student, Accurate predictions of slugs in multiphase pipe flow simulation for improved oil and gas production
  • ― CWI-INRIA collaboration (PI: E. Camporeale CWI), 2014, Ph.D. student, Data-enhanced simulations for Space Weather predictions
  • ― Shell-NWO/FOM program (PI), 2014, Ph.D. student, Probabilistic uncertainty assessments in energy-related problems
  • ― NWO MPE program (PI), 2014, Ph.D. student, Geometric structure and data assimilation
  • ― NWO Rubicon (PI), 2009, Statistical bias of numerical discretizations and data assimilation in geophysical fluid dynamics


  • Jurriaan Buist, Ph.D. 2019-2023 (co-supervision with Benjamin Sanderse)
  • Bart de Leeuw, Ph.D. 2015-2019
  • Sangeetika Ruchi, Ph.D. U. Utrecht, 2020, thesis pdf
  • Mandar Chandorkar, Ph.D. TU Delft, 2019 (co-supervision with Enrico Camporeale), thesis pdf
  • Gido Limperg, Bachelor UvA, 2018, thesis pdf
  • Kaj-Ivar van der Wijst, Bachelor U. Utrecht, 2016, thesis pdf

Collaborations and international network


In preparation

  • ― S. Ruchi, S. Dubinkina and J. de Wiljes, "Fast hybrid tempered ensemble transform filter formulation for Bayesian elliptical problems via Sinkhorn approximation", preprint.
  • ― B. de Leeuw and S. Dubinkina, "Ensemble shadowing-based data assimilation method".
  • ― B. de Leeuw and S. Dubinkina, "Shadowing-based data assimilation method for partially observed models", preprint.

Published articles

  • ― S. Dubinkina and S. Ruchi, "Comparison of Regularized Ensemble Kalman Filter and Tempered Ensemble Transform Particle Filter for an elliptic inverse problem with uncertain boundary conditions", Computational Geosciences, (2019), https://doi.org/10.1007/s10596-019-09904-w, preprint.
  • ― S. Ruchi, S. Dubinkina and M.A. Iglesias, "Transform-based particle filtering for elliptic Bayesian inverse problems", Inverse Problems 35 115005 (2019), https://doi.org/10.1088/1361-6420/ab30f3, preprint.
  • ― S. Ruchi and S. Dubinkina, "Application of ensemble transform data assimilation methods for parameter estimation in reservoir modeling", Nonlin. Processes Geophys., 25 (2018), pp. 731–746, https://doi.org/10.5194/npg-25-731-2018, article.
  • ― B. de Leeuw, S. Dubinkina, J. Frank, A. Steyer, X. Tu and E. Van Vleck, "Projected Shadowing-based Data Assimilation", SIAM J. Appl. Dyn. Syst., 17(4) (2018), pp. 2446–2477, https://doi.org/10.1137/17M1141163, preprint.
  • ― S. Dubinkina, "Relevance of conservative numerical schemes for an Ensemble Kalman Filter", Q.J.R. Meteorol. Soc., 144 (2018), pp.467-477, doi:10.1002/qj.3219
  • ― V. Zunz, H. Goosse and S. Dubinkina, "Impact of the initialization on the predictability of Southern Ocean sea ice at interannual to multi-decadal timescales", Climate Dynamics, 44 (2015), pp. 2267–2286.
  • ― A. Mairesse, H. Goosse, P. Mathiot, H. Wanner and S. Dubinkina, ”Investigating the consistency between proxies and between proxies and models using data assimilation: a mid-Holocene case study”, Clim. Past, 9 (2013), pp. 2741–2757.
  • ― S. Dubinkina and H. Goosse, ”An assessment of particle filtering methods and nudging for climate state reconstructions”, Clim. Past, 9 (2013), pp. 1141–1152.
  • ― P. Mathiot, H. Goosse, X. Crosta, B. Stenni, M. Braida, H. Renssen, C.J. Van Meerbeeck, V. Masson-Delmotte, A. Mairesse and S. Dubinkina, ”Using data assimilation to investigate the causes of Southern Hemisphere high latitude cooling from 10 to 8 ka BP”, Clim. Past, 9 (2013), pp. 887–901.
  • ― H. Goosse, E. Crespin, S. Dubinkina, M.F. Loutre, M.E. Mann, H. Renssen, Y. Sallaz-Damaz and D. Shindell, ”The role of forcing and internal dynamics in explaining the medieval climate anomaly”, Climate Dynamics, 39 (2012), pp. 2847–2866.
  • ― H. Goosse, J. Guiot, M.E. Mann, S. Dubinkina and Y. Sallaz-Damaz, ”The medieval climate anomaly in Europe: comparison of the summer and annual mean signals in two reconstructions and in simulations with data assimilation”, Global and Planetary Change 84–85 (2012), pp. 35–47.
  • ― S. Dubinkina, H. Goosse, Y. Sallaz-Damaz, E. Crespin and M. Crucifix, ”Testing a particle filter to reconstruct climate changes over the past centuries”, International Journal of Bifurcation and Chaos 21(12) (2011), pp. 3611– 3618.
  • ― S. Dubinkina, J. Frank and B. Leimkuhler, ”Simplified Modelling of a Thermal Bath, with Application to a Fluid Vortex System”, SIAM Multiscale Model. Simul. 8 (2010), pp. 1882–1901.
  • ― S. Dubinkina and J. Frank, ”Statistical relevance of vorticity conservation with the Hamiltonian particle-mesh method”, J. Comput. Phys. 229 (2010), pp. 2634–2648.
  • ― S. Dubinkina and J. Frank, ”Statistical mechanics of Arakawa’s discretizations”, J. Comput. Phys. 227 (2007), pp. 1286–1305.
  • ― V. Pukhnachev and S. Dubinkina, ”A model of film deformation and rupture under the action of thermo- capillary forces”, Fluid Dynamics 41(5) (2006), pp. 755–771.

PhD thesis

  • ― S.Dubinkina, "Statistical mechanics and numerical modelling of geophysical fluid dynamics”, University of Amsterdam, 28 May 2010, pdf

Media coverage

  • ― Article in NRC Handelsblad (national Dutch newspaper) about my PhD research "Het klimaat en het weer voorspellen blijkt nog weer moeilijker", 5 juni 2010, article


Current courses

Analysis I at VU Amsterdam (study guide 2020-2021)

Dynamics and Computation at VU Amsterdam (study guide 2020-2021)

Mathematcial Modelling of Dynamical Systems at VU Amsterdam (study guide 2020-2021)

Past courses

Scientific Computing Seminar at Utrecht University (spring 2016, fall 2017)

Teaching Assistant for ”Physique générale et éléments de mathématique 1” at Université catholique de Louvain (fall 2011)


Organiser of

Upcoming meetings

Past meetings


VU Amsterdam

1081 HV Amsterdam | De Boelelaan 1111 | room 09A43 | +31(0)20 5987700 | s dot b dot dubinkina at vu dot nl