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Irina Zhelavskaya

PhD students


Biography

In 2012, Irina graduated from the Department of Cybernetics and Information Security of Moscow Engineering Physics Institute, Russia, and started her double-degree Masters program at Skolkovo Institute of Science and Technology (Skoltech), Russia, and Moscow Institute of Physics and Technology (MIPT), Russia. During that time she did 1.5 years long exchange program at MIT as a visiting student. In 2015, she defended her MSc thesis “Deriving Electron Density from Electric Field Measurements on the Van Allen Probes Spacecraft” summa cum laude. Irina started working as staff research associate at the University of California, Los Angeles (UCLA), USA, at 2015. Prior to that she worked at the Center of Optical Neural Technologies of Scientific Research Institute for System Analysis, Russian Academy of Sciences.

Research interests

  • Neural networks
  • Data analysis

Publications

  1. Shprits Y. Y., H. J. Allison, D. Wang, A. Drozdov, M. Szabo-Roberts, I. Zhelavskaya, R. Vasile, (2022), A New Population of Ultra-Relativistic Electrons in the Outer Radiation Zone, J. Geophys. Res. [Space Physics], 127, e2021JA030214, doi:10.1029/2021JA030214, e2021JA030214 2021JA030214
  2. Landis D. A., A. A. Saikin, I. Zhelavskaya, A. Y. Drozdov, N. Aseev, Y. Y. Shprits, M. F. Pfitzer, A. G. Smirnov, (2022), NARX Neural Network Derivations of the Outer Boundary Radiation Belt Electron Flux, Space Weather, 20, e2021SW002774, doi:10.1029/2021SW002774, e2021SW002774 2021SW002774
  3. Saikin A. A., Y. Y. Shprits, A. Y. Drozdov, D. A. Landis, I. S. Zhelavskaya, S. Cervantes Villa, (2021), Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017), Space Weather, 19, e2020SW002524, doi:10.1029/2020SW002524
  4. Allison H. J., Y. Y. Shprits, I. S. Zhelavskaya, D. Wang, A. G. Smirnov, (2021), Gyroresonant wave-particle interactions with chorus waves during extreme depletions of plasma density in the Van Allen radiation belts, Science Advances, 7, doi:10.1126/sciadv.abc0380
  5. Zhelavskaya I. S., N. A. Aseev, Y. Y. Shprits, (2021), A Combined Neural Network- and Physics-Based Approach for Modeling Plasmasphere Dynamics, J. Geophys. Res. [Space Physics], 126, e2020JA028077, doi:10.1029/2020JA028077, e2020JA028077 2020JA028077
  6. Smirnov A., Y. Shprits, I. Zhelavskaya, H. Luhr, C. Xiong, A. Goss, F. S. Prol, M. Schmidt, M. Hoque, N. Pedatella, M. Szabó-Roberts, (2021), Intercalibration of the Plasma Density Measurements in Earth’s Topside Ionosphere, J. Geophys. Res. [Space Physics], 126, e29334, doi:10.1029/2021JA029334
  7. Jackson D. R., S. Bruinsma, S. Negrin, C. Stolle, C. J. Budd, R. Dominguez Gonzalez, E. Down, D. J. Griffin, M. J. Griffith, G. Kervalishvili, D. Lubi’an Arenillas, J. Manners, J. Matzka, Y. Y. Shprits, R. Vasile, I. S. Zhelavskaya, (2020), The Space Weather Atmosphere Models and Indices (SWAMI) project: Overview and first results, J. Space Weather Space Clim., 10, 18, doi:10.1051/swsc/2020019
  8. Smirnov A. G., M. Berrendorf, Y. Y. Shprits, E. A. Kronberg, H. J. Allison, N. A. Aseev, I. S. Zhelavskaya, S. K. Morley, G. D. Reeves, M. R. Carver, F. Effenberger, (2020), Medium Energy Electron Flux in Earth’s Outer Radiation Belt (MERLIN): A Machine Learning Model, Space Weather, 18, e2020SW002532, doi:10.1029/2020SW002532, e2020SW002532 10.1029/2020SW002532
  9. Sarma R., M. Chandorkar, I. Zhelavskaya, Y. Shprits, A. Drozdov, E. Camporeale, (2020), Bayesian Inference of Quasi-Linear Radial Diffusion Parameters using Van Allen Probes, J. Geophys. Res. [Space Physics], 125, e2019JA027618, doi:10.1029/2019JA027618, e2019JA027618 10.1029/2019JA027618
  10. Wang D., Y. Y. Shprits, I. S. Zhelavskaya, F. Effenberger, A. Castillo, A. Y. Drozdov, N. Aseev, S. Cervantes Villa, (2020), The Effect of Plasma Boundaries on the Dynamic Evolution of Relativistic Radiation Belt Electrons, J. Geophys. Res. [Space Physics], n/a, e2019JA027422, doi:10.1029/2019JA027422, e2019JA027422 2019JA027422
  11. Shprits Y. Y., R. Vasile, I. S. Zhelavskaya, (2019), Nowcasting and Predicting the Kp Index Using Historical Values and Real-Time Observations, Space Weather, 17, 1219-1229, doi:10.1029/2018SW002141
  12. Zhelavskaya I. S., R. Vasile, Y. Y. Shprits, C. Stolle, J. Matzka, (2019), Systematic Analysis of Machine Learning and Feature Selection Techniques for Prediction of the Kp Index, Space Weather, 17, 1461-1486, doi:10.1029/2019SW002271
  13. Wang D., Y. Y. Shprits, I. S. Zhelavskaya, O. V. Agapitov, A. Y. Drozdov, N. A. Aseev, (2019), Analytical Chorus Wave Model Derived from Van Allen Probe Observations, J. Geophys. Res. [Space Physics], 124, 1063-1084, doi:10.1029/2018JA026183
  14. Green J. C., Y. Y. Shprits, E. Haggarty, T. Onsager, I. Zhelavskaya, (2018), Summary of Stakeholder Inputs on Development of a Satellite Anomaly Database From the European Space Weather Week, Space Weather, 16, 343-344, doi:10.1029/2018SW001823
  15. Liemohn M. W., J. P. McCollough, V. K. Jordanova, C. M. Ngwira, S. K. Morley, C. Cid, W. K. Tobiska, P. Wintoft, N. Y. Ganushkina, D. T. Welling, S. Bingham, M. A. Balikhin, H. J. Opgenoorth, M. A. Engel, R. S. Weigel, H. J. Singer, D. Buresova, S. Bruinsma, I. S. Zhelavskaya, Y. Y. Shprits, R. Vasile, (2018), Model Evaluation Guidelines for Geomagnetic Index Predictions, Space Weather, 16, 2079-2102, doi:10.1029/2018SW002067
  16. Shprits Y. Y., I. S. Zhelavskaya, J. C. Green, A. A. Pulkkinen, R. B. Horne, D. Pitchford, T. P. O’Brien, A. Glover, (2018), Discussions on Stakeholder Requirements for Space Weather-Related Models, Space Weather, 16, 341-342, doi:10.1002/2018SW001864
  17. Saikin A. A., V. K. Jordanova, J. C. Zhang, C. W. Smith, H. E. Spence, B. A. Larsen, G. D. Reeves, R. B. Torbert, C. A. Kletzing, I. S. Zhelavskaya, Y. Y. Shprits, (2018), Comparing simulated and observed EMIC wave amplitudes using in situ Van Allen Probes’ measurements, Journal Of Atmospheric And Solar-terrestrial Physics, 177, doi:10.1016/j.jastp.2018.01.024
  18. Cao X., Y. Y. Shprits, B. Ni, I. S. Zhelavskaya, (2017), Scattering of Ultra-relativistic Electrons in the Van Allen Radiation Belts Accounting for Hot Plasma Effects, Scientific Reports, 7, 17719, doi:10.1038/s41598-017-17739-7
  19. Aseev N. A., Y. Y. Shprits, A. Y. Drozdov, A. C. Kellerman, M. E. Usanova, D. Wang, I. S. Zhelavskaya, (2017), Signatures of Ultrarelativistic Electron Loss in the Heart of the Outer Radiation Belt Measured by Van Allen Probes, J. Geophys. Res. [Space Physics], 122, 10,102-10,111, doi:10.1002/2017JA024485
  20. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojević, (2017), Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks, J. Geophys. Res. [Space Physics], 122, 11,227-11,244, doi:10.1002/2017JA024406
  21. Shprits Y. Y., A. Y. Drozdov, M. Spasojevic, A. C. Kellerman, M. E. Usanova, M. J. Engebretson, O. V. Agapitov, I. S. Zhelavskaya, T. J. Raita, H. E. Spence, D. N. Baker, H. Zhu, N. A. Aseev, (2016), Wave-induced loss of ultra-relativistic electrons in the Van Allen radiation belts, Nature Communications, 7, doi:10.1038/ncomms12883
  22. Zhelavskaya I. S., M. Spasojevic, Y. Y. Shprits, W. S. Kurth, (2016), Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft, J. Geophys. Res. [Space Physics], 121, 4611-4625, doi:10.1002/2015JA022132
  23. Zhelavskaya I., V. Kryzhanovsky, M. Malsagov, (2015), Error Probability for Scalar Neural Network Trees in High-Dimensional Binary Space, doi:10.4108/icst.bict.2014.257924
  1. Zhelavskaya I. S., N. A. Aseev, Y. Y. Shprits, (2021), A Combined Neural Network- and Physics-Based Approach for Modeling Plasmasphere Dynamics, J. Geophys. Res. [Space Physics], 126, e2020JA028077, doi:10.1029/2020JA028077, e2020JA028077 2020JA028077
  2. Zhelavskaya I. S., R. Vasile, Y. Y. Shprits, C. Stolle, J. Matzka, (2019), Systematic Analysis of Machine Learning and Feature Selection Techniques for Prediction of the Kp Index, Space Weather, 17, 1461-1486, doi:10.1029/2019SW002271
  3. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojević, (2017), Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks, J. Geophys. Res. [Space Physics], 122, 11,227-11,244, doi:10.1002/2017JA024406
  4. Zhelavskaya I. S., M. Spasojevic, Y. Y. Shprits, W. S. Kurth, (2016), Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft, J. Geophys. Res. [Space Physics], 121, 4611-4625, doi:10.1002/2015JA022132
  5. Zhelavskaya I., V. Kryzhanovsky, M. Malsagov, (2015), Error Probability for Scalar Neural Network Trees in High-Dimensional Binary Space, doi:10.4108/icst.bict.2014.257924
  1. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Chapter 12 – Reconstruction of Plasma Electron Density From Satellite Measurements Via Artificial Neural Networks, Elsevier, 9780128117880, doi:10.1016/B978-0-12-811788-0.00012-3
  2. Kryzhanovskiy V., I. Zhelavskaya, (2015), Double-Layer Vector Perceptron for Binary Patterns Recognition, Springer International Publishing, 978-3-319-09903-3

Conference presentations

  1. Zhelavskaya I. S., Y. Y. Shprits, N. Aseev, M. Spasojevic, (2019), Application of Geomagnetic Indices to the Plasmasphere Modeling, (invited), 27th IUGG General Assembly, July 8–18, 2019, Montréal, Québec, Canada
  2. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2019), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics, (poster), EGU General Assembly 2019, April 8 – 13, 2019, Vienna, Austria
  3. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2018), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics during extreme geomagnetic events, AGU 2018 Fall Meeting, December 9 – 14, 2018, Washington D.C, USA
  4. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2018), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics, (invited), The Plasmasphere And The Warm Plasma Cloak Workshop, September 18–20, 2018, Los Alamos, NM, USA.
  5. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Modelling the global plasmasphere dynamics using neural network- and physics-based approaches, 42nd Cospar Scientific Assembly, July 14–22, 2018, Pasadena, CA, USA
  6. Zhelavskaya I. S., Y. Y. Shprits, R. Vasile, C. Stolle, J. Matzka, (2018), Systematic analysis of machine learning techniques for Kp prediction in the framework of the H2020 project SWAMI, 42nd Cospar Scientific Assembly, July 14–22, 2018, Pasadena, CA, USA
  7. Zhelavskaya I. S., Y. Y. Shprits, (2018), International standard for validating the Kp index predictive models, 42nd Cospar Scientific Assembly, July 14–22, 2018, Pasadena, CA, USA
  8. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Prediction of the dynamics of the plasmasphere, (invited), EGU General Assembly 2018, April 8–13, 2018, Vienna, Austria
  9. Zhelavskaya I. S., Y. Y. Shprits, R. Vasile, C. Stolle, J. Matzka, (2018), Systematic analysis of machine learning techniques for Kp prediction, (poster), EGU General Assembly 2018, April 8–13, 2018, Vienna, Austria
  10. Zhelavskaya I. S., Y. Shprits, M. Spasojevic, (2017), Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks, AGU 2017 Fall Meeting
  11. Zhelavskaya I., Y. Shprits, M. Spasojevic, (2017), Global dynamic evolution of the cold plasma inferred with neural networks, EGU General Assembly 2017, EGU2017 proceedings from the conference held 23-28 April, 2017 in Vienna, Austria., p.2320
  12. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, European Space Weather Week, November 27 – December 1, 2017, Ostend, Belgium.
  13. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, (invited), Space Weather: A Multi-Disciplinary Approach Workshop, September 25–29, 2017, Lorentz Center, Leiden, the Netherlands
  14. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Deriving electron density from electric field measurements on the Van Allen Probes spacecraft and building a global dynamic model of plasma density using neural networks, (invited), IAPSO-IAMAS-IAGA Assembly, August 27 – September 1, 2017, Cape Town, South Africa
  15. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, (talk, poster), GEM Summer Workshop 2017, June 18–23, 2017, Portsmouth, VA, USA
  16. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere with neural networks, (invited), POF PT I Workshop: From Atmosphere To Space Weather, May 30, 2017, Potsdam, Germany
  17. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Global dynamic evolution of the cold plasma inferred with neural networks, DGG 2017, March 27–30, 2017, Potsdam, Germany
  18. Zhelavskaya I., M. Spasojevic, Y. Shprits, W. Kurth, (2016), NURD: Neural-network-based Upper-hybrid Resonance Determination algorithm, GEM Summer Workshop 2016
  19. Zhelavskaya I., M. Spasojevic, Y. Shprits, W. Kurth, (2016), Automated Determination of Electron Density from Electric Field Measurements on the Van Allen Probes Spacecraft, EGU General Assembly 2016, Abstract presented at 2016 EGU General Assembly, Vienna, Austria, 17-22 April.
  20. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2016), Global dynamic evolution of the cold plasma inferred with neural networks, AGU Fall Meeting 2016, San Francisco, 12-16 December
  21. Zhelavskaya I., W. Kurth, M. Spasojevic, Y. Shprits, (2016), Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft, 41st Cospar Scientific Assembly, abstracts from the meeting that was to be held 30 July – 7 August at the Istanbul Congress Center(ICC), Turkey, but was cancelled.,Abstract id.# PRBEM.1-3-16.
  22. Zhelavskaya I. S., M. Spasojevic, Y. Shprits, (2015), Automated Determination of Electron Density from Electric Field Measurements on the Van Allen Probes Spacecraft, AGU Fall Meeting 2015, San Francisco, CA, 14-18 December
  23. Zhelavskaya I., V. Kryzhanovsky, M. Malsagov, (2015), Error Probability for Scalar Neural Network Trees in High-Dimensional Binary Space, doi:10.4108/icst.bict.2014.257924
  1. Zhelavskaya I. S., Y. Y. Shprits, N. Aseev, M. Spasojevic, (2019), Application of Geomagnetic Indices to the Plasmasphere Modeling, (invited), 27th IUGG General Assembly, July 8–18, 2019, Montréal, Québec, Canada
  2. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2018), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics, (invited), The Plasmasphere And The Warm Plasma Cloak Workshop, September 18–20, 2018, Los Alamos, NM, USA.
  3. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Prediction of the dynamics of the plasmasphere, (invited), EGU General Assembly 2018, April 8–13, 2018, Vienna, Austria
  4. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, (invited), Space Weather: A Multi-Disciplinary Approach Workshop, September 25–29, 2017, Lorentz Center, Leiden, the Netherlands
  5. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Deriving electron density from electric field measurements on the Van Allen Probes spacecraft and building a global dynamic model of plasma density using neural networks, (invited), IAPSO-IAMAS-IAGA Assembly, August 27 – September 1, 2017, Cape Town, South Africa
  6. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere with neural networks, (invited), POF PT I Workshop: From Atmosphere To Space Weather, May 30, 2017, Potsdam, Germany
  1. Shprits Y., H. Allison, A. Drozdov, D. Wang, N. Aseev, I. Zhelavskaya, M. Usanova, (2021), Controlling Effect of the Cold Plasma Density on Acceleration and Loss of Electrons at Ultra-Relativistic Energies, AGU 2021 Fall Meeting, SM12A-02
  2. Saikin A., Y. Shprits, A. Drozdov, D. Landis, I. Zhelavskaya, J. S. Cervantes Villa, (2021), Reconstruction of the Radiation Belts for Solar Cycles 17-24 (1933-2017), AGU 2021 Fall Meeting, SH45E-2409
  3. Wang D., Y. Shprits, A. Drozdov, I. Zhelavskaya, F. Effenberger, A. M. Castillo Tibocha, (2021), Simulations of the Relativistic Radiation Belt Electrons Using the VERB-3D Code, 3rd ISEE Symposium, ISEE, Nagoya University, Japan, March 8-12, 2021
  4. SHPRITS Y., H. ALLISON, A. DROZDOV, D. WANG, N. ASEEV, I. ZHELAVSKAYA, M. USANOVA, (2021), Acceleration and Loss of Ultra-relativistic Electrons in the Earth Van Allen Radiation Belts, (invited), AOGS 2021
  5. Drozdov A., Y. Shprits, N. Aseev, M. Usanova, F. Effenberger, H. Allison, A. Saikin, I. Zhelavskaya, (2021), Depletion of multi-MeV electrons and its relation to the minima in phase space density, 43rd COSPAR Scientific Assembly, Sydney, Australia, 28 Jan – 04 Feb 2021
  6. Shprits Y., H. Allison, A. Drozdov, D. Wang, N. Aseev, I. Zhelavskaya, M. Usanova, (2021), Acceleration and Loss of Ultra-relativistic Electrons in the Earth Van Allen Radiation Belts, EGU General Assembly 2021, EGU General Assembly Conference Abstracts, EGU21-3120
  7. Wang D., Y. Shprits, A. Drozdov, N. Aseev, I. Zhelavskaya, A. Castillo, H. Allison, S. Cervantes Villa, F. Effenberger, (2021), Simulations of the Relativistic Radiation Belt Electrons Using the VERB-3D Code, EGU General Assembly 2021, EGU General Assembly Conference Abstracts, EGU21-3802
  8. Kume K., I. Zhelavskaya, Y. Shprits, A. Smirnov, R. Vasile, S. Bianco, (2021), A systematic approach for modeling global VTEC using machine learning, EGU General Assembly 2021, EGU General Assembly Conference Abstracts, EGU21-16167
  9. Smirnov A., E. Kronberg, F. Effenberger, G. Reeves, S. Morley, Y. Shprits, N. Aseev, I. Zhelavskaya, M. Carver, H. Allison, M. Berrendorf, (2021), Medium energy electron flux in Earth’s outer radiation belt (MERLIN): a machine learning model from GPS data, 43rd COSPAR Scientific Assembly, 1086
  10. Wang D., Y. Shprits, I. Zhelavskaya, A. Drozdov, N. Aseev, F. Effenberger, A. Castillo, S. Cervantes Villa, (2020), Controlling Effect of Wave Models and Plasma Boundaries on the Dynamic Evolution of Relativistic Radiation Belt Electrons, EGU General Assembly 2020, EGU General Assembly Conference Abstracts, 17946
  11. Shprits Y., N. Aseev, A. Drozdov, J. S. Cervantes Villa, A. M. Castillo Tibocha, I. Zhelavskaya, R. Vasile, F. Effenberger, D. Soergel, I. Michaelis, A. Saikin, (2020), Modeling and Data Assimilation of the Ring Current, Relativistic and Ultra-relativistic Electrons in the Inner Magnetosphere, EGU General Assembly 2020, EGU General Assembly Conference Abstracts, 3354
  12. Wang D., Y. Shprits, I. Zhelavskaya, F. Effenberger, A. Drozdov, A. M. Castillo Tibocha, N. Aseev, J. S. Cervantes Villa, (2020), Controlling Effect of Wave Models and Plasma Boundaries on the Dynamic Evolution of Relativistic Radiation Belt Electrons, AGU 2020 Fall Meeting
  13. Drozdov A., Y. Shprits, N. Aseev, M. Usanova, H. Allison, A. Saikin, I. Zhelavskaya, (2020), Minima in phase space density and how they relate to the multi-MeV electron radiation belt depletions, AGU 2020 Fall Meeting
  14. Saikin A., Y. Shprits, A. Drozdov, D. Landis, I. Zhelavskaya, J. S. Cervantes Villa, (2020), Reconstruction of the Radiation Belts for Solar Cycles 17 – 24 (1933 – 2017), AGU 2020 Fall Meeting,
  15. Shprits Y., H. Allison, A. Drozdov, D. Wang, N. Aseev, I. Zhelavskaya, M. Usanova, (2020), Acceleration and Loss of Ultra-relativistic Electrons in the Earth Van Allen Radiation Belts, AGU 2020 Fall Meeting
  16. Landis D., I. Zhelavskaya, Y. Shprits, N. Aseev, (2019), Neural Network-Based Model of Radiation Belt Electron Flux Near GEO, AGU 2019 Fall Meeting
  17. Shprits Y., N. Aseev, A. Drozdov, J. S. Cervantes Villa, A. M. Castillo, I. Zhelavskaya, R. Vasile, F. Effenberger, D. Boneberg, I. Michaelis, A. Saikin, (2019), Modeling and Data Assimilation of the Ring Current, Relativistic and Ultra-relativistic Electrons in the Inner Magnetosphere, AGU 2019 Fall Meeting
  18. Shprits Y., A. Drozdov, N. Aseev, A. Kellerman, M. Usanova, I. Zhelavskaya, I. Michaelis, J. S. Cervantes Villa, W. Dedong, A. Castillo, (2019), Deepening Minimums in PSD as Evidence of the Localized Loss of Electrons by EMIC waves, GEM Summer Workshop 2019
  19. Zhelavskaya I. S., Y. Y. Shprits, N. Aseev, M. Spasojevic, (2019), Application of Geomagnetic Indices to the Plasmasphere Modeling, (invited), 27th IUGG General Assembly, July 8–18, 2019, Montréal, Québec, Canada
  20. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2019), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics, (poster), EGU General Assembly 2019, April 8 – 13, 2019, Vienna, Austria
  21. Castillo A. M., Y. Shprits, F. Effenberger, D. Wang, I. Zhelavskaya, N. Aseev, A. Drozdov, J. S. Cervantes Villa, R. Vasile, I. Michaelis, (2019), Modeling electron dynamics in the inner magnetosphere, EGU General Assembly 2019, EGU General Assembly Conference Abstracts, 12405
  22. Wang D., Y. Shprits, I. Zhelavskaya, O. Agapitov, A. Drozdov, N. Aseev, S. Cervantes Villa, A. Castillo, F. Yao, (2019), Controlling Effect of Wave Models and Plasmapause Position on the Dynamic Evolution of Radiation Belt Electrons, EGU General Assembly 2019, EGU General Assembly Conference Abstracts, 9362
  23. Aseev N., Y. Shprits, A. Kellerman, A. Drozdov, M. Usanova, D. Wang, I. Zhelavskaya, (2018), Observational evidence of ultra-relativistic electron scattering from the earth’s radiation belts, 42nd Cospar Scientific Assembly
  24. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2018), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics during extreme geomagnetic events, AGU 2018 Fall Meeting, December 9 – 14, 2018, Washington D.C, USA
  25. Zhelavskaya I. S., N. Aseev, Y. Y. Shprits, M. Spasojevic, (2018), A combined neural network- and physics-based approach for modeling the plasmasphere dynamics, (invited), The Plasmasphere And The Warm Plasma Cloak Workshop, September 18–20, 2018, Los Alamos, NM, USA.
  26. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Modelling the global plasmasphere dynamics using neural network- and physics-based approaches, 42nd Cospar Scientific Assembly, July 14–22, 2018, Pasadena, CA, USA
  27. Zhelavskaya I. S., Y. Y. Shprits, R. Vasile, C. Stolle, J. Matzka, (2018), Systematic analysis of machine learning techniques for Kp prediction in the framework of the H2020 project SWAMI, 42nd Cospar Scientific Assembly, July 14–22, 2018, Pasadena, CA, USA
  28. Zhelavskaya I. S., Y. Y. Shprits, (2018), International standard for validating the Kp index predictive models, 42nd Cospar Scientific Assembly, July 14–22, 2018, Pasadena, CA, USA
  29. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Prediction of the dynamics of the plasmasphere, (invited), EGU General Assembly 2018, April 8–13, 2018, Vienna, Austria
  30. Zhelavskaya I. S., Y. Y. Shprits, R. Vasile, C. Stolle, J. Matzka, (2018), Systematic analysis of machine learning techniques for Kp prediction, (poster), EGU General Assembly 2018, April 8–13, 2018, Vienna, Austria
  31. Shprits Y., D. Wang, M. Spasojevic, I. Zhelavskaya, A. Drozdov, N. Aseev, (2018), A New Analytical Chorus Wave Model Derived from Van Allen Probe Observations, AGU 2018 Fall Meeting, SM43D-3604
  32. Aseev N., Y. Shprits, A. Kellerman, A. Drozdov, D. Wang, I. Zhelavskaya, (2018), New signatures of EMIC wave-driven loss of ultrarelativistic electrons in the heart of the outer radiation belt, EGU General Assembly 2018, EGU General Assembly Conference Abstracts, 1360
  33. Zhelavskaya I. S., Y. Shprits, M. Spasojevic, (2017), Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks, AGU 2017 Fall Meeting
  34. Shprits Y., I. S. Zhelavskaya, A. C. Kellerman, M. Spasojevic, D. A. Kondrashov, M. Ghil, N. Aseev, A. M. Castillo Tibocha, J. S. Cervantes Villa, C. Kletzing, W. S. Kurth, (2017), Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools, AGU 2017 Fall Meeting
  35. Zhelavskaya I., Y. Shprits, M. Spasojevic, (2017), Global dynamic evolution of the cold plasma inferred with neural networks, EGU General Assembly 2017, EGU2017 proceedings from the conference held 23-28 April, 2017 in Vienna, Austria., p.2320
  36. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, European Space Weather Week, November 27 – December 1, 2017, Ostend, Belgium.
  37. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, (invited), Space Weather: A Multi-Disciplinary Approach Workshop, September 25–29, 2017, Lorentz Center, Leiden, the Netherlands
  38. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Deriving electron density from electric field measurements on the Van Allen Probes spacecraft and building a global dynamic model of plasma density using neural networks, (invited), IAPSO-IAMAS-IAGA Assembly, August 27 – September 1, 2017, Cape Town, South Africa
  39. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere dynamics using neural networks, (talk, poster), GEM Summer Workshop 2017, June 18–23, 2017, Portsmouth, VA, USA
  40. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Empirical modeling of the plasmasphere with neural networks, (invited), POF PT I Workshop: From Atmosphere To Space Weather, May 30, 2017, Potsdam, Germany
  41. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2017), Global dynamic evolution of the cold plasma inferred with neural networks, DGG 2017, March 27–30, 2017, Potsdam, Germany
  42. Zhelavskaya I., M. Spasojevic, Y. Shprits, W. Kurth, (2016), NURD: Neural-network-based Upper-hybrid Resonance Determination algorithm, GEM Summer Workshop 2016
  43. Zhelavskaya I., M. Spasojevic, Y. Shprits, W. Kurth, (2016), Automated Determination of Electron Density from Electric Field Measurements on the Van Allen Probes Spacecraft, EGU General Assembly 2016, Abstract presented at 2016 EGU General Assembly, Vienna, Austria, 17-22 April.
  44. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2016), Global dynamic evolution of the cold plasma inferred with neural networks, AGU Fall Meeting 2016, San Francisco, 12-16 December
  45. Zhelavskaya I., W. Kurth, M. Spasojevic, Y. Shprits, (2016), Automated determination of electron density from electric field measurements on the Van Allen Probes spacecraft, 41st Cospar Scientific Assembly, abstracts from the meeting that was to be held 30 July – 7 August at the Istanbul Congress Center(ICC), Turkey, but was cancelled.,Abstract id.# PRBEM.1-3-16.
  46. Zhelavskaya I. S., M. Spasojevic, Y. Shprits, (2015), Automated Determination of Electron Density from Electric Field Measurements on the Van Allen Probes Spacecraft, AGU Fall Meeting 2015, San Francisco, CA, 14-18 December
  47. Zhelavskaya I., V. Kryzhanovsky, M. Malsagov, (2015), Error Probability for Scalar Neural Network Trees in High-Dimensional Binary Space, doi:10.4108/icst.bict.2014.257924

Seminars

  1. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Modeling the plasmasphere electron density: from local Van Allen Probe observations to the global plasmasphere dynamics, Los Alamos National Laboratory, Los Alamos, NM, USA, September, 17, 2018
  2. Zhelavskaya I. S., Y. Y. Shprits, M. Spasojevic, (2018), Reconstruction of electron density from satellite measurements and Empirical modelling of the plasmasphere dynamics using neural networks, Van Allen Probes SWG Telecon, APL, January, 5, 2018