Evgeny Burnaev

Evgeny’s current research focuses on the development of new algorithms in machine learning and artificial intelligence such as deep networks for the

• approximation of physical models,
• generative modeling, and manifold learning,

with applications to

• computer vision and 3D reconstruction,
• neurovisualization

1. I. Udovichenko, E. Shvetsov, D. Divitsky, D. Osin, I. Trofimov, I. Sukharev, A. Glushenko, D. Berestnev, E. Burnaev. SeqNAS: Neural Architecture Search for Event Sequence Classification. IEEE Access, vol. 12, pp. 3898-3909, 2024, doi: 10.1109/ACCESS.2024.3349497. (Q1)
2. D. Shadrin, S. Illarionova, F. Gubanov, K. Evteeva, M. Mironenko, I. Levchunets, R. Belousov & E. Burnaev. Wildfire spreading prediction using multimodal data and deep neural network approach. Sci Rep 14, 2606 (2024). https://doi.org/10.1038/s41598-024-52821-x (Q1)
3. A. Korotin, N. Gushchin, E. Burnaev. Light Schrödinger Bridge. ICLR, 2024. (Core A*)
4. P. Mokrov, A. Korotin, A. Kolesov, N. Gushchin, E. Burnaev. Energy-guided Entropic Neural Optimal Transport. ICLR, 2024. (Core A*)
5. A. Asadulaev, A. Korotin, V. Egiazarian, P. Mokrov, E. Burnaev. Neural Optimal Transport with General Cost Functionals. ICLR, 2024. (Core A*)
6. N. Gushchin, S. Kholkin, E. Burnaev, A. Korotin. Light and Optimal Schrödinger Bridge Matching. ICML, 2024
7. Kolesov, P. Mokrov, I. Udovichenko, M. Gazdieva, G. Pammer, E. Burnaev, A. Korotin. Estimating Barycenters of Distributions with Neural Optimal Transport. ICML, 2024
8. Balabin, D. Voronkova, I. Trofimov, E. Burnaev, S. Barannikov. Disentanglement Learning via Topology. ICML, 2024
9. Shumilin, A. Ryabov, N. Yavich, E. Burnaev, V. Vanovskiy. Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation. ICML, 2024.
10. N. Yavich, V. Vanovskiy, A. Okunev, A. Gavrikov, T. Grigoryev, E. Burnaev. A physics-inspired neural network for short-wave radiation parameterization. J. Inverse Ill-Posed Probl., 2024.
11. F. Skomorokhov, J. Wang, G. Ovchinnikov, E. Burnaev, I. Oseledets. An event-triggered iteratively reweighted convex optimization approach to multi-period portfolio selection. Expert Systems with Applications, 2023. (Q1)
12. I. Trofimov, N. Klyuchnikov, M. Salnikov, A. Filippov and E. Burnaev. Multi-fidelity Neural Architecture Search with Knowledge Distillation. IEEE Access, 2023. (Q1)
13. M.O. Zubrikhina, O.V. Abramova, V.E. Yarkin, V.L. Ushakov, A.G. Ochneva, A.V. Bernstein, E.V. Burnaev, D.S. Andreyuk, V.B. Savilov, M.V. Kurmishev, T.S. Syunyakov, O.A. Karpenko, A.V. Andryushchenko, G.P. Kostyuk, M.G. Sharaev. Machine learning approaches to mild cognitive impairment detection based on structural MRI data and morphometric features. Cognitive Systems Research, Vol. 78, pp. 87-95, 2023. (Q1)
14. Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev. Kernel Neural Optimal Transport. ICLR, 2023. (Core A*)
15. Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev. Neural Optimal Transport. ICLR, Notable-top-25% paper, 2023. (Core A*)
16.  Ilya Trofimov, Daniil Cherniavskii, Eduard Tulchinskii, Nikita Balabin, Evgeny Burnaev, Serguei Barannikov. Learning Topology-Preserving Data Representations. ICLR, 2023. (Core A*)
17. Oleg Voynov, Gleb Bobrovskikh, Pavel Karpyshev, Saveliy Galochkin, Andrei-Timotei Ardelean, Arseniy Bozhenko, Ekaterina Karmanova, Pavel Kopanev, Yaroslav Labutin-Rymsho, Ruslan Rakhimov, Aleksandr Safin, Valerii Serpiva, Alexey Artemov, Evgeny Burnaev, Dzmitry Tsetserukou, Denis Zorin. Multi-sensor large-scale dataset for multi-view 3D reconstruction. CVPR, 2023. (Core A*)
18. Andreea Dogaru, Andrei Timotei Ardelean, Savva Ignatyev, Evgeny Burnaev, Egor Zakharov. Sphere-Guided Training of Neural Implicit Surfaces. CVPR, 2023. (Core A*)
19. Amal Bouzid; Abdulrahman Al Midani; Maria Zubrikhina; Altyngul Kamzanova; Burcu Yener Ilce; Manzura Zholdassova; Ayesha M Yusuf; Poorna Manasa Bhamidimarri; Hamid A. AlHaj; Almira Kustubayeva; Alexander Bernstein; Evgeny Burnaev; Maxim Sharaev. Integrative Bioinformatics and Artificial Intelligence Analyses of Transcriptomics Data Identified Genes Associated with Major Depressive Disorders including NRG1. Neurobiology of Stress, 2023. (Q1)
20. Burnaev, E., Mironov, E., Shpilman, A., Mironenko, M., & Katalevsky, D. Practical AI Cases for Solving ESG Challenges. MDPI Sustainability, 15(17), 12731, 2023. https://doi.org/10.3390/su151712731 (Q1)
21. Bulygin I, Shatov V, Rykachevskiy A, Raiko A, Bernstein A, Burnaev E, Gelfand MS. Absence of enterotypes in the human gut microbiomes reanalyzed with non-linear dimensionality reduction methods. PeerJ 11:e15838, 2023. http://doi.org/10.7717/peerj.15838 (Q1)
22. Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva, Daniil Cherniavskii, Sergey Nikolenko, Evgeny Burnaev, Serguei Barannikov, Irina Piontkovskaya. Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts. NeurIPS, 2023 (Core A*)
23. Daria Voronkova, Serguei Barannikov, Evgeny Burnaev. 1-dimensional Topological Invariants to Estimate Loss Surface Non-Convexity. Doklady Mathematics, 2023. (Q2)
24. Serguei Barannikov, Alexander Korotin, Dmitry Oganesyan, Daniil Emtsev, Evgeny Burnaev. Barcodes as summary of loss function topology. Doklady Mathematics, 2023. (Q2)
25. Vladislav Zhuzhel, Vsevolod Grabar, Nina Kaploukhay, Rodrigo Rivera-Castro, Liliya Mironova, Alexey Zaytsev, Evgeny Burnaev. No Two Users are Alike: Generating Audiences with Neural Clustering for Temporal Point Processes. Doklady Mathematics, 2023. (Q2)
26. Illarionova, S.; Shadrin, D.; Shukhratov, I.; Evteeva, K.; Popandopulo, G.; Sotiriadi, N.; Oseledets, I.; Burnaev, E. Benchmark for Building Segmentation on Up-Scaled Sentinel-2 Imagery. Remote Sens. 2023, 15, 2347. https://doi.org/10.3390/rs15092347 (Q1)
27. Rakhimov, Burkov, Safin, Burnaev, Lempitskiy. Multi-NeuS: 3D Head Portraits from Single Image with Neural Implicit Functions. IEEE Access, 2023 (Q1)
28. Georgii Popandopulo, Svetlana Illarionova, Dmitrii Shadrin, Ksenia Evteeva, Nazar Sotiriadi and Evgeny Burnaev. Flood extension and volume estimation using remote sensing data. Remote Sensing, 2023. (Q1)
29. Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva, Daniil Cherniavskii, Serguei Barannikov, Irina Piontkovskaya, Sergey Nikolenko4, Evgeny Burnaev. Topological Data Analysis for Speech Processing. Interspeech, 2023 (Core A)
30. Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry Vetrov, Evgeny Burnaev. Entropic Neural Optimal Transport via Diffusion Processes. NeurIPS, 2023 (Oral talk, 2% of accepted papers) (Core A*)
31. Milena Gazdieva, Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev. Extremal Domain Translation with Neural Optimal Transport. NeurIPS, 2023 (Core A*)
32. Nikita Gushchin, Alexander Kolesov, Petr Mokrov, Polina Karpikova, Andrey Spiridonov, Evgeny Burnaev, Alexander Korotin. Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark. NeurIPS, 2023 (Core A*)
33. Roman Kail, Alexey Zaytsev, Evgeny Burnaev. Recurrent Convolutional Neural Networks help to predict location of Earthquakes, Vol. 19, pp. 1-5, IEEE Geoscience and Remote Sensing Letters, 2022. (Q1)
34. A. Lange, A. Stepanov, E. Burnaev, A. Somov. Building a Behavioral Profile and Assessing the Skill of Video Game Players. IEEE Sensors Journal, Volume: 22, Issue: 1, pp. 481-488 2022. (Q1)
35. D. Volkhonskiy, E. Muravleva, O. Sudakov, D. Orlov, B. Belozerov, E. Burnaev, D. Koroteev. Generative Adversarial Networks for Reconstruction of 3D porous media from 2D slices. Physical Review E, 2022 (Q1)
36. Valentina Bachurina , Svetlana Sushchinskaya, Maxim Sharaev, Evgeny Burnaev, Marie Arsalidou. A machine learning investigation of factors that contribute to predicting cognitive performance: Difficulty level, reaction time and eye-movements. Journal of Decision Support Systems, 2022 (Q1)
37. Marie Arsalidou, Nikolay Skuratov, Evgeny Khalezov, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev. Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers. PLOS ONE, 2022 (Q1)
38. Ivan Fursov, Alexey Zaytsev, Pavel Burnyshev, Dmitrieva Ekaterina, Nikita Klyuchnikov, Andrey Kravchenko, Ekaterina Artemova and Evgeny Burnaev. A Differentiable Language Model Adversarial Attack on Text Classifiers. IEEE Access, 2022 (Q1)
39. Albert Matveev, Alexey Artemov, Ruslan Rakhimov, Gleb Bobrovskikh, Daniele Panozzo, Denis Zorin, Evgeny Burnaev. DEF: Deep Estimation of Sharp Geometric Features in 3D Shapes. ACM Transactions on Graphics (TOG), Siggraph, 2022 (Q1)
40. Litu Rout, Alexander Korotin, Evgeny Burnaev. Generative Modeling with Optimal Transport Maps. ICLR, 2022 (Core A*)
41. Ivan Fursov, Alexey Zaytsev, Rasul Khasianov, Martin Spindler, Evgeny Burnaev. Sequence embeddings help to identify fraudulent cases in healthcare insurance. IEEE Access, 2022 (Q1)
42. N. Klyuchnikov, E. Artemova, M. Fedorov, I. Trofimov, M. Salnikov, E. Burnaev. NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing. IEEE Access, 2022 (Q1)
43. O. Tsimboy, Y. Kapushev, E. Burnaev, I. Oseledets. Denoising Score Matching via Random Fourier Features. IEEE Access, 2022 (Q1)
44. Y. Shen, Z. Du, H. Fu, X. Chen, E. Burnaev, D. Zorin, K. Zhou, Y. Zheng. GCNDenoiser: Feature-preserving Mesh Denoising with Graph Neural Networks. ACM Transactions on Graphics (TOG) 41(1), 1-14, ACM, 2022/2/10 (Q1)
45. Ruslan Rakhimov, Andrei-Timotei Ardelean, Victor Lempitsky, Evgeny Burnaev. NPBG++: Accelerating Neural Point-Based Graphics. CVPR, 2022 (Core A*)
46. Serguei Barannikov, Ilya Trofimov, Nikita Balabin, Evgeny Burnaev. Representation Topology Divergence: A Method for Comparing Neural Network Representations. ICML, 2022 (Core A*)
47. Alexander Korotin, Alexander Kolesov, Evgeny Burnaev. Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? Neurips, 2022 (Core A*)
48. Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev. Wasserstein Iterative Networks for Barycenter Estimation. Neurips, 2022. (Core A*)
49. Daniil Cherniavskii, Eduard Tulchinskii, Vladislav Mikhailov, Irina Proskurina, Laida Kushnareva, Ekaterina Artemova, Serguei Barannikov, Irina Piontkovskaya, Dmitri Piontkovski and Evgeny Burnaev. Acceptability Judgements via Examining the Topology of Attention Maps. EMNLP, 2022. (Core A)
50. Anton Smerdov, Andrey Somov, Evgeny Burnaev & Anton Stepanov. AI-enabled Prediction of Video Game Player Performance Using the Data from Heterogeneous Sensors. Multimedia Tools and Applications, 2022. (Q1)
51. Svetlana Illarionova, Polina Tregubova, Vladimir Ignatiev, Albert Efimov, Ivan Oseledets and Evgeny Burnaev. A Survey of Computer Vision Techniques for Forest Characterization and Carbon Monitoring Tasks. Remote Sens., 14(22), 5861, 2022. (Q1)
52. A. Mikhaylov, N. Mazyavkina, M. Salnikov, I. Trofimov, F. Qiang, E. Burnaev. Learned Query Optimizers: Evaluation and Improvement. IEEE Access, 2022. (Q1)
53. Timofey Grigoryev, Polina Verezemskaya, Mikhail Krinitskiy, Nikita Anikin, Alexander Gavrikov, Ilya Trofimov, Nikita Balabin, Aleksei Shpilman, Andrei Eremchenko, Sergey Gulev, Evgeny Burnaev, Vladimir Vanovskiy. Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting. Remote Sens., 14(22), 2022. (Q1)
54. Alexander Korotin, Lingxiao Li, Justin Solomon, Evgeny Burnaev. Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization. ICLR, 2021 (Core A*)
55.  Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev. Wasserstein-2 Generative Networks. ICLR, 2021 (Core A*)
56. Korotin A.A., Vyugin V.V., Burnaev E.V. Online algorithm for aggregating experts’ predictions with unbounded quadratic loss. Russian Mathematical Surveys, 2021, 75(5), pp. 974–977 (Q1)
57. Alexey Bokhovkin, Vladislav Ishimtsev, Emil Bogomolov, Denis Zorin, Alexey Artemov, Evgeny Burnaev, Angela Dai. Towards Part-Based Understanding of RGB-D Scans. CVPR, 2021 (Core A*)
58. A. Smerdov, A. Somov, E. Burnaev, B. Zhou and P. Lukowicz, “Detecting Video Game Player Burnout With the Use of Sensor Data and Machine Learning,” in IEEE Internet of Things Journal, vol. 8, no. 22, pp. 16680-16691, 15 Nov.15, 2021, doi: 10.1109/JIOT.2021.3074740. (Q1)
59. Nina Mazyavkina, Sergey Sviridov; Sergei Ivanov; Evgeny Burnaev. Reinforcement Learning for Combinatorial Optimization: A Survey. Computers and Operations Research, 2021 (Q1)
60. Burnaev E., Bernstein A. Functional Dimension Reduction in Predictive Modeling, Journal of communications technology and electronics, 2021. Vol. 66, No. 6, p. 745-753 (English), http://www.jip.ru/2020/317-329-2020.pdf (Russian version) (Q4)
61. Burnaev E., Bernstein A. Manifold Modeling in Machine Learning, Journal of communications technology and electronics, 2021. Vol. 66, No. 6 (English), http://www.jip.ru/2020/342-356-2020.pdf (Russian version) (Q4)
62. R Rakhimov, E Bogomolov, A Notchenko, F Mao, A Artemov, D Zorin, Evgeny Burnaev. Making DensePose fast and light. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 1869-1877, 2021 (Core A). https://arxiv.org/abs/2006.15190
63. Matvey Morozov, Ivan Fursov, Alexey Zaytsev, Nina Kaploukhaya, Elizaveta Kovtun, Rodrigo Rivera. Gleb Gusev, Dmitry Babaev, Ivan Kireev, Evgeny Burnaev. Adversarial Attacks on Deep Models for Financial Transaction Records. KDD, 2021 (Core A*)
64. Y. Kapushev, A. Kishkun, G. Ferrer and E. Burnaev, “Random Fourier Features based SLAM,” 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 6597-6602, doi: 10.1109/IROS51168.2021.9636819 (Core A)
65. Simon Abramov, Alexander Korotin, Andrey Somov, Evgeny Burnaev, Anton S. Abramov, A. Korotin, A. Somov, E. Burnaev, A. Stepanov, D. Nikolaev, M. Titova,”Analysis of Video Game Players’ Emotions and Team Performance: an eSports Tournament Case Study,” in IEEE Journal of Biomedical and Health Informatics, pp. 1-8. doi: 10.1109/JBHI.2021.3119202. RFBR grant no. 18-29-23077. (Q1)
66. Ivan Makhotin, Denis Orlov, Dmitry Koroteev, Evgeny Burnaev, Aram Karapetyan, Dmitry Antonenko. Machine learning for recovery factor estimation of an oil reservoir: a tool for de-risking at a hydrocarbon asset evaluation. Journal: Petroleum, 2021 (Q2)
67. Anton Rykachevsky, Alexander Stepakov, Polina Muzyukina, Sofia Medvedeva, Mark Dobrovolski, Evgeny Burnaev, Konstantin Severinov, Ekaterina Savitskaya. SCRAMBLER: tool for de novo CRISPR array reconstruction and its application for analysis of structure of prokaryotic populations. The CRISPR Journal, 2021 (Q4)
68. Korotin, A., V’yugin, V., & Burnaev, E. Integral mixabilty: a tool for efficient online aggregation of functional and probabilistic forecasts. Journal Pattern Recognition, 2021 (Q1)
69. Laida Kushnareva, Daniil Cheriavskii, Vladislav Mikhailov, Ekaterina Artemova, Serguei Barannikov, Alexander Bernstein, Irina Piontkovskaya, Dmitri Piontkovski, Evgeny Burnaev. Artificial Text Detection via Examining the Topology of Attention Maps. EMNLP, oral talk, 2021 (Core A)
70. Evgenii Egorov, Anna Kuzina, Evgeny Burnaev. BooVAE: Boosting Approach for Continual Learning of VAE. NeurIPS, 2021 (Core A*)
71. Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev. Manifold Topology Divergence: a Framework for Comparing Data Manifolds. NeurIPS, 2021 (Core A*)
72. Petr Mokrov, Alexander Korotin, Lingxiao Li, Aude Genevay, Justin Solomon, Evgeny Burnaev. Large-Scale Wasserstein Gradient Flows. NeurIPS, 2021 (Core A*)
73. Alexander Korotin, Lingxiao Li, Aude Genevay, Justin Solomon, Alexander Filippov, Evgeny Burnaev. Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark. NeurIPS, 2021 (Core A*)
74. V.M. Duplyakov, A.D. Morozov, D.O. Popkov, E.V. Shel, A.L. Vainshtein, E.V. Burnaev, A.A. Osiptsov. Data-driven model for hydraulic fracturing design optimization. Part II: Inverse problem. Journal of Petroleum Science and Engineering, 2021. (Q1)
75. Rodrigo Rivera-Castro, Evgeny Burnaev. CAUSALYSIS: Causal Machine Learning for Real-Estate Investment Decisions. 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA), 2021, pp. 1-3, doi: 10.1109/DSAA53316.2021.9564210. (Core A)
76. Vage Egiazarian, Oleg Voynov, Alexey Artemov, Denis Volkhonskiy, Aleksandr Safin, Maria Taktasheva, Denis Zorin, Evgeny Burnaev. Deep Vectorization of Technical Drawings. ECCV 2020 (Core A*)
77. Vladislav Ishimtsev, Alexey Bokhovkin, Alexey Artemov, Savva Ignatyev, Matthias Niessner, Denis Zorin, Evgeny Burnaev. CAD-Deform: Deformable Fitting of CAD Models to 3D Scans. ECCV 2020 (Core A*)
78. A. Korotin, V. Vyugin, E. Burnaev. Adaptive Hedging under Delayed Feedback. Neurocomputing, Volume 397, 15 July 2020, Pages 356-368. (Q1)
79. N. Klyuchnikov, E. Burnaev. Gaussian process Classification for Variable Fidelity Data. Neurocomputing, Volume 397, 15 July 2020, Pages 345-355. (Q1)
80.  Potapova S.G., Artemov A.V., Sviridov S.V., Musatkina D.A., Zorin D.N., Burnaev E.V. Next Best View Planning via Reinforcement Learning for Scanning of arbitrary 3D Shapes. Journal of communications technology and electronics, 2020. Vol. 65, No. 12, pp. 1484–1490 (English) (Q4)
81. Ivan Nazarov, Evgeny Burnaev. Bayesian Sparsification of Deep C-valued networks. Proceedings of ICML, 2020 (Core A*)
82. Y. Kapushev, I. Oseledets, E. Burnaev. Tensor Completion via Gaussian Process based Initialization. SIAM Journal on Scientific Computing 42(6), A3812-A3824, Society for Industrial and Applied Mathematics, 2020. (Q1)
83. Anton D. Morozov, Dmitry O. Popkov, Victor M. Duplyakov, Renata F. Mutalova, Andrei A. Osiptsov, Albert L. Vainshtein, Evgeny V. Burnaev, Egor V. Shel, Grigory V. Paderin. Data-driven model for hydraulic fracturing design optimization: focus on building digital database and production forecast. Journal of Petroleum Science and Engineering. Volume 194, November 2020, 107504 (Q1)
84. E. Romanenkova, A. Zaytsev, N. Klyuchnikov, A. Gruzdev, K. Antipina, L. Ismailova, E. Burnaev, A. Semenikhin, V. Koryabkin, I. Simon, D. Koroteev. Real-time data-driven detection of the rock type alteration during a directional drilling. IEEE Geoscience and Remote Sensing Letters, Vol. 17, Issue 11, p. 1861-1865, 2020. (Q1)

• Excellence Recognition Award from Skoltech president, 2022
• Best cooperation project leader award from Huawei, 2021
• Best Paper Award for the research on modeling of point clouds and predicting properties of 3D shapes at the Int. Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), 2020
• Ilya Segalovich Yandex Science Prize (“The best research director of postgraduate students in the field of computer sciences”), 2020
• Geometry Processing Dataset Award for the work “ABC Dataset: A Big CAD Model Dataset For Geometric Deep Learning”, Symposium on Geometry Processing, 2019
• Best Paper Award for the research in eSports at the IEEE Internet of People conference, 2019
• Moscow Government Prize for Young Scientists in the category for the Transmission, Storage, Processing and Protection of Information for leading the project “The development of methods for predictive analytics for processing industrial, biomedical and financial data”, 2017

PhD thesis defended under the supervision of Prof. Burnaev

1. 2023 “Computational methods for understanding large-scale 3D scenes at the level of parts of objects”. Dissertation for the degree of Candidate of Computer Science. Author: Ishimtsev Vladislav Igorevich. Dissertation was defended at the Board of HSE Computer Science Council
2. 2023 “Deep generative learning for image sequence modeling”. Dissertation for the degree of Candidate of Computer Science. Author: Denis Alekseevich Volkhonsky. Dissertation was defended at the Board of HSE Computer Science Council
3. 2023 “Parametric methods for calculating optimal transport maps, distances and barycenters”. Dissertation for the degree of Candidate of Physical and Mathematical Sciences: speciality 1.2.2. mathematical modeling, numerical methods and software systems. Author: Alexander Andreevich Korotin. Dissertation was defended at the Board 24.1.224.01 of FRC CSC RAS
4. 2022 “Restoration of geometric properties of three-dimensional shapes by machine learning methods with application to engineering tasks”. Dissertation for the degree of Candidate of Physical and Mathematical Sciences: speciality 1.2.2. mathematical modeling, numerical methods and software systems. Author: Albert Antonovich Matveev. Dissertation was defended at the Board FPMI.1.2.2.011 of MIPT
5. 2021 “Multi-fidelity classification and active search”. PhD: PhD Program «Computational and Data Science and Engineering». Author: Nikita Klyuchnikov. PhD was defended at the Board of Skolkovo Institute of Science and Technology
6. 2021 “Gaussian process models for large-scale problems”. PhD: PhD Program «Computational and Data Science and Engineering». Author: Ermek Kapushev. PhD was defended at the Board of Skolkovo Institute of Science and Technology
7. 2019 “Combinatorial and neural graph vector representations”. PhD: PhD Program «Computational and Data Science and Engineering». Author: Sergey Ivanov. PhD was defended at the Board of Skolkovo Institute of Science and Technology.
8. 2017 “Mathematical models of time-series with trends in quickest change-point detection problems”. Dissertation for the degree of Candidate of Physical and Mathematical Sciences: speciality 05.13.18, mathematical modeling, numerical methods and software systems. Author: Artemov Alexey Valeryevich. Dissertation was defended at the Board D 002.073.04 of FRC CSC RAS
9. 2017 “Methods for construction of regression models based on heterogenuous data sources for industrial engineering”. Dissertation for the degree of Candidate of Physical and Mathematical Sciences: speciality 05.13.18, mathematical modeling, numerical methods and software systems. Author: Zaytsev Alexey Alexeevich. Dissertation was defended at the Board D 002.077.05 of IITP
10. 2013 “Application of Methods for Experts Aggregation and Regression based on Gaussian Processes for construction of Metamodels”. Dissertation for the degree of Candidate of Physical and Mathematical Sciences: speciality 05.13.17, theoretical foundations of informatics. Author: Prikhodko Pavel Viktorovich. Dissertation was defended at the Board D 212.156.04 of MIPT

• Machine Learning, an obligatory course for the 1st year Master students in Data Science
• Bayesian methods of Machine Learning, an elective course for the 1st/2nd year Master students in Data Science
• Foundations of Data Science, an elective course for Ph.D. students

• Евгений Бурнаев о нейросетях, искусственном интеллекте и научном прогнозировании // Час Speak [In Russian]
• Evgeny Burnaev: Will we create a terminator some day? Maybe.

ФИО: Бурнаев Евгений Владимирович

Занимаемая должность: профессор

Преподаваемые дисциплины: Машинное обучение, Байесовские методы машинного обучения, Основы наук о данных

Ученая степень:

• Кандидат физико-математических наук, 2008, Институт проблем передачи информации им. А.А. Харкевича РАН (05.13.17 – теоретические основы информатики)
• Доктор физико-математических наук, 2022, Московский физико-техничесий институт (05.13.18 – Мат. моделирование, численные методы и комплексы программ)

Ученое звание (при наличии): Доцент

Общий стаж работы: более 18 лет

Стаж работы по специальности: более 18 лет