Mathematical modeling, Mathematical Statistics, Intelligent Data Analysis, Machine Learning
Biography
Graduated from the Moscow State University, Department of Mechanics and Mathematics, USSR/Russia, in 1969, where he obtained his Master degree in mathematics.
Alexander started his career in developing mathematical models and algorithms for computer networks. At the same time, he was doing research in mathematical statistics. For research in this field he received the Candidate of Sciences Degree in Physics and Mathematics (analog of PhD degree) from Steklov Mathematical Institute of USSR Academy of Sciences in 1973 and the Doctor of Sciences degree in Physics and Mathematics in 1987 from the Department of Computational Mathematics and Cybernetics of Moscow State University. In the year of 1991, the USSR Higher Attestation Commission awarded Alexander with the academic rank of Professor in the field of Intelligent Technologies and Systems.
In 2002, Alexander joined the Software Engineering Center of the Russian Academy of Sciences to lead the projects in developing data analysis and applied mathematics software. Prior to joining Skoltech, Alexander held the positions of Chief Researcher at the Institute for System Analysis RAS and Lead Scientist in the Data Analysis Research Lab at the Institute for Information Transmission Problems RAS.
At the same time, he had part-time full professor positions at National Research University Higher School of Economics and Moscow Institute of Physics and technology. Author of more than 150 scientific publications, among them more than 25 publications indexed in WoS/Scopus in the last three years. Since 2016, he is Professor of the Practice at Skoltech.
Today, Alexander’s research interests encompass the area of theoretical foundations of Data science (Mathematical modeling, Mathematical Statistics, Intelligent Data Analysis, Machine Learning) with a focus on applied tasks of Computational Neuroscience.
Kuleshov A.P., Bernstein A.V., “Nonlinear multi-output regression on unknown input manifold.”, Annals of Mathematics and Artificial Intelligence, 81:1-2 (2017), 209-240
Bernstein A.V., Kuleshov A.P., “Manifold Learning: generalizing ability and tangent proximity”, International Journal of Software and Informatics, 7:3 (2013), 359-390
Bernstein A.V., Kuleshov A.P., Yanovich Yu.A., “Manifold Learning in Regression tasks”, Statistical Learning and Data Sciences (Statistical Learning and Data Sciences, London, 2015), Lecture Notes in Artificial Intelligence, 9407, Springer International Publishing, Switzerland, 2015, 414-423
Kuleshov A.P., Bernstein A.V., Burnaev E.V., “Conformal Prediction in Manifold Learning”, Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications (Seventh Workshop on Conformal and Probabilistic Prediction and Applications, Stockholm, 2018), Proceedings of Machine Learning Research, 91, 2018, 234-253
E. V. Burnaev, A. V. Bernshtein, V. V. Vanovskiy, A. A. Zaytsev, A. M. Bulkin, V. Yu. Ignatiev, D. G. Shadrin, S. V. Illarionova, I. V. Oseledets, A. Yu. Mikhalev, A. A. Osiptsov, A. A. Artemov, M. G. Sharaev, I. E. Trofimov, “Fundamental research and developments in the field of applied artificial intelligence”, Dokl. RAN. Math. Inf. Proc. Upr., 508 (2022), 19–27; Dokl. Math., 106:suppl. 1 (2022), S14–S22
A. P. Kuleshov, A. V. Bernstein, Yu. A. Yanovich, “Manifold learning based on kernel density estimation”, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 160:2 (2018), 327–338
3.
A. V. Bernstein, “Manifold learning in statistical tasks”, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 160:2 (2018), 229–242
2012
4.
Ju. G. Agalakov, A. V. Bernstein, “Data dimensionality reduction in simulation modeling”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2012, no. 3, 3–17
2008
5.
A. V. Bernshtein, A. P. Kuleshov, “Когнитивные технологии в проблеме снижения размерности описания геометрических объектов”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2008, no. 2, 6–19
6.
A. V. Bernshtein, A. P. Kuleshov, “Optimal Filtering of a Random Background in Image Processing Problems”, Probl. Peredachi Inf., 44:3 (2008), 70–80; Problems Inform. Transmission, 44:2 (2008), 233–242
A. V. Bernshtein, Yu. L. Tomfield, I. V. Shagaev, “Storage Unit with High Reliability Characteristics. I”, Avtomat. i Telemekh., 1992, no. 3, 145–152
1986
8.
A. V. Bernstein, “Asymptotically complete classes of tests in the multivariate case with asymptotic expansions”, Teor. Veroyatnost. i Primenen., 31:1 (1986), 67–80; Theory Probab. Appl., 31:1 (1987), 58–71
1985
9.
A. V. Bernštein, “A refinement of theorems on complete classes of tests”, Teor. Veroyatnost. i Primenen., 30:3 (1985), 576–580; Theory Probab. Appl., 30:3 (1986), 613–617
10.
A. V. Bernštein, “On asymptotically complete classes of tests in the problem of testing composite hypotheses under the contiguite alternatives”, Teor. Veroyatnost. i Primenen., 30:1 (1985), 78–91; Theory Probab. Appl., 30:1 (1986), 87–102
A. V. Bernštein, “Uniformity classes in problems of testing composite hypotheses”, Teor. Veroyatnost. i Primenen., 29:4 (1984), 787–791; Theory Probab. Appl., 29:4 (1985), 823–827
A. V. Bernshtein, “Testing of composite statistical hypotheses from samples of large size”, Izv. Vyssh. Uchebn. Zaved. Mat., 1983, no. 11, 3–18; Soviet Math. (Iz. VUZ), 27:11 (1983), 1–20
13.
A. V. Bernštein, “The structure of the class of absolutely admissible tests”, Teor. Veroyatnost. i Primenen., 28:2 (1983), 404–410; Theory Probab. Appl., 28:2 (1984), 426–432
A. V. Bernšhteĭn, “The testing of composite hypotheses with nuisance parameters in multidimensional case”, Teor. Veroyatnost. i Primenen., 25:2 (1980), 291–302; Theory Probab. Appl., 25:2 (1981), 287–298
A. V. Bernštein, “On the construction of majorizing tests”, Teor. Veroyatnost. i Primenen., 25:1 (1980), 18–29; Theory Probab. Appl., 25:1 (1980), 16–26
A. V. Bernshtein, “Asymptotically similar criteria”, Itogi Nauki i Tekhniki. Ser. Teor. Veroyatn. Mat. Stat. Teor. Kibern., 17 (1979), 3–56; J. Soviet Math., 17:3 (1981), 1825–1857
A. V. Bernšteĭn, “On asymptotically optimal tests for composite hypotheses under non-standard conditions”, Teor. Veroyatnost. i Primenen., 21:1 (1976), 34–47; Theory Probab. Appl., 21:1 (1976), 34–47
A. V. Bernshtein, “Asymptotic properties of group estimators of a random collection”, Teor. Veroyatnost. i Primenen., 19:1 (1974), 219–223; Theory Probab. Appl., 19:1 (1974), 212–215
1972
20.
A. V. Bernstein, A. A. Sidorov, “Estimates of the set of expectations for a normal population”, Teor. Veroyatnost. i Primenen., 17:4 (1972), 768–773; Theory Probab. Appl., 17:4 (1973), 723–726
A. V. Bernstein, A. A. Sidorov, “On characteristic properties of Fisher's $k$-statistics”, Teor. Veroyatnost. i Primenen., 17:4 (1972), 766–768; Theory Probab. Appl., 17:4 (1973), 721–723
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