- Research Professor:Faculty of Computer Science / Department of Complex System Modelling Technologies
- Chief Research Fellow:Faculty of Computer Science / International Laboratory of Stochastic Algorithms and High-Dimensional Inference
- Programme Scientific Supervisor:Math of Machine Learning
- Vladimir Spokoiny has been at HSE University since 2015.
Education, Degrees and Academic Titles
Doctor of Sciences*
Candidate of Sciences* (PhD)
Moscow Institute of Engineers of Railroad Transport
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.
A post-doctoral degree called Doctor of Sciences is given to reflect second advanced research qualifications or higher doctorates in ISCED 2011.
- Modern Methods of Decision Making: Advanced Statistical Methods (Master’s programme; Faculty of Computer Science; 1 year, 4 module)Eng
2011–// Megagrant of Russian Governement, 150M RUB
2013-2016 International Research Training Group “High Dimensional Non Stationary Time Series”, (1 PhD position); 2012–2015 DFG Research Unit 1735 “Structural Inference in Statistics: Adaptation and Efficiency”. (1 PostDoc position);
2002–2014 DFG Forschungszentrum “Mathematic for Key Technologies”, Project A3 “Image and signal processing in medicine and biosciences” (1 PostDoc position);
2002–2014 DFG Forschungszentrum “Mathematic for Key Technologies”, Project E5 “Applied Mathematical Finance” (2 PhD position).
2005–2016 DFG Collaborative Research Center 649 “Economic risk” Project B5 “Structure adaptive data analysis” (1 PostDoc position).
2001–2006 DFG-Priority Program 1114 “Mathematical methods for time series analysis and digital image processing”, Project “Structural adaptive smoothing procedures with applications in imaging and functional MRI” (1 PostDoc position).
2000–2003 BMBF-F¨orderprogramm“ Neue Mathematische Verfahren in Industrie und Dienstleistung”. Project “Efficient Methods for Evaluation of Risk” joint with Bankgesellschaft Berlin AG, (2 PhD position). 2000–2004 Berliner Graduiertenkolleg “Stochastic Processes and Probabilistic Analysis”. (1 PhD position).
1993–2003 SFB 373 “Quantification and Simulation of “Economic Processes”, Humboldt Universit”at zu Berlin; project B1 (2.5 PhD position). Industry grants 2006–2007 WGZ Bank D¨usseldorf (1 PhD position)
2007–2010 Landesbank Berlin (1 PhD position). 2007–2014 Nordbank Hamburg–Kiel (1 PhD position). Offers 1999 Purdue University, Full professorship, declined 1999 W¨urzburg Universit¨at, Lehrstuhl, C4, declined 2000 Wien Universit¨at, ordentliche Professur, declined 3 2001 Humboldt Universit¨at zu Berlin, S-Professur, accepted
Organizer and Member of Programm Committee of various conferences and workshops.
Chair for various sessions of conferences and workshops
- Article Kroshnin A., Spokoiny V., Suvorikova A. Statistical inference for Bures-Wasserstein barycenters // Annals of Applied Probability. 2021. Vol. 31. No. 3. P. 1264-1298. doi
- Article Puchkin N., Spokoiny V. An adaptive multiclass nearest neighbor classifier // ESAIM: Probability and Statistics. 2020. Vol. 24. P. 69-99. doi
- Article Bachoc F., Suvorikova A., Ginsbourger D., Loubes J., Spokoiny V. Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding // Electronic journal of statistics. 2020. Vol. 14. No. 2. P. 2742-2772. doi
- Article Naumov A., Spokoiny V., Ulyanov V. V. Bootstrap confidence sets for spectral projectors of sample covariance // Probability Theory and Related Fields. 2019. Vol. 174. No. 3-4. P. 1091-1132. doi
- Article Goetze F., Naumov A., Spokoiny V., Ulyanov V. V. Large ball probability, Gaussian comparison and anti-concentration // Bernoulli: a journal of mathematical statistics and probability. 2019. Vol. 25. No. 4(A). P. 2538-2563. doi
- Book Spokoiny V., Suvorikova A. Topics in Applied Analysis and Optimisation Partial Differential Equations, Stochastic and Numerical Analysis. Springer, 2019. doi
- Article Silin I., Spokoiny V. Bayesian inference for spectral projectors of the covariance matrix // Electronic journal of statistics. 2018. Vol. 12. No. 1. P. 1948-1987. doi
- Article Naumov A., Spokoiny V., Ulyanov V. V. Confidence Sets for Spectral Projectors of Covariance Matrices / Пер. с рус. // Doklady Mathematics. 2018. Vol. 98. No. 2. P. 511-514. doi
- Article Naumov A., Spokoiny V., Ulyanov V. V., Tavyrikov Y. Nonasymptotic Estimates for the Closeness of Gaussian Measures on Balls, / Пер. с рус. // Doklady Mathematics. 2018. Vol. 98. No. 2. P. 490-493. doi
- Article Spokoiny V. Penalized maximum likelihood estimation and effective dimension // Annales de l'institut Henri Poincare (B) Probability and Statistics. 2017. Vol. 53. No. 1. P. 389-429. doi
- Article Andresen A., Spokoiny V. Convergence of an alternating maximization procedure // Journal of Machine Learning Research. 2016. No. 17(63). P. 1-53.
- Article Kalinina A., Suvorikova A., Spokoiny V., Gelfand M. S. Detection of homologous recombination in closely related strains // Journal of Bioinformatics and Computational Biology. 2016. Vol. 14. No. 2. P. 1641001-1-1641001-12. doi
- Article Spokoiny V., Zhilova M. Bootstrap confidence sets under model misspecification // Annals of Statistics. 2015. Vol. 43. No. 6. P. 2653-2675.
- Preprint Anikin A., Dvurechensky P., Gasnikov A., Golov A., Gornov A., Maximov Y., Mendel M., Spokoiny V. Efficient numerical algorithms for regularized regression problem with applications to traffic matrix estimations / Cornell University. Series arXiv "math". 2015.
- Article Panov M., Spokoiny V. Critical Dimension in Semiparametric Bernstein – von Mises Theorem / Пер. с рус. // Proceedings of the Steklov Institute of Mathematics. 2014. Vol. 287. No. 1. P. 232-255. doi
1981 - 1984 - Researcher. All-Union Institute of Railway Transport, Moscow, Russia.
1988 -1990 - Senior researcher. All-Union Institute of Railway Transport, Moscow, Russia.
Since 1990 - Senior researcher. Institute for Information Transmission Problems, Russian Academy of Sciences, Russia.
1993 - 1997 - Senior researcher. Institute for Applied Analysis and Statistics, Berlin, Germany.
1997 - 1998 - Associate Professor. Humboldt University, Berlin, Germany.
1998 - 1999 - Senior researcher. Institute for Applied Analysis and Statistics, Berlin, Germany.
1999 - 2000 - Professor, University of Wurzburg, Wurzburg,
Since 2020 - Head of Research Group, Weierstrass-Institute, Berlin, Germany.
Since 2002 - Professor at the Humboldt University, Berlin.
Since 2013 - Professor at the Lomonosov University, Moscow.
Since 2013 - Professor at the University of Physics and Technology, Moscow.
Hamidreza Behjoo graduated from the Statistical Learning Theory master’s programme with distinction. Currently, he is a PhD student in Applied mathematics at the University of Arizona. We asked him about his experience of the master’s programme, the courses he found the most useful, and his impressions of Moscow.
On October 26-30, Statistics, Artificial Intelligence, Machine Learning, Probability, Learning Theory Event (SAMPLE) conference took place in Gelendzhik, Russia.
Until April 20, you can apply to take part in the Math of Machine Learning 2021 contest. The winners of the contest will be able to enrol into HSE University's Math of Machine Learning master's programme and Skoltech's Data Science master's programme (Math of Machine Learning track) without entrance exams.
HSE University’s Faculty of Computer Science and Skoltech have organised Statistical Learning Theory Olympiad for the third time. The Olympiad’s main award is admission to the HSE University and Skoltech joint master’s programme.
Students who wish to compete in the Statistical Learning Theory Olympiad held jointly by HSE University and Skoltech may apply until March 16. Winners of the Olympiad automatically gain admittance to the joint HSE-Skoltech Master’s Programme in Statistical Learning Theory. HSE News Service spoke with last year’s winners about their experience competing in the Olympiad and now studying in the joint programme.
HDI Lab staff attend International Vilnius Conference on Probability Theory and Mathematical Statistics 2018
12th International Vilnius Conference on Probability Theory and Mathematical Statistics and 2018 IMS Annual Meeting on Probability and Statistics took place in Vilnius (Lithuania) on July 2-6. This is one of the world's leading conferences in the field of modern probability theory and mathematical statistics, which is held every four years since 1973. This year over 200 works were presented at the event and 500 participants from all over the globe attended it.
Attracted by the famous mathematical education in Russia, Alfredo Alejandro De la Fuente Briceño decided to travel halfway around the world to enrol in HSE’s Master’s Programme in Statistical Learning Theory, a new joint programme between HSE and Skoltech aimed at training the next generation of scientists to carry out fundamental research and work on challenging new problems in statistical learning theory. After completing his Bachelor’s degree in Petroleum and Natural Gas Engineering at the National University of Engineering in Lima, Peru, the 25-year-old was encouraged by several professors and friends to try a programme in a different language and tradition and step outside his comfort zone.
Team of researchers of the HSE International Laboratory of Stochastic Algorithms and High-Dimensional Inference was announced as a winner of the Russian Science Foundation Grant Competition to support fundamental and exploratory scientific research conducted by individual scientific groups and was awarded three-year grant for implementation of the project "Analysis of high dimensional random objects with applications to large scale data processing" (RSF №18-11-00132).
HSE Lends Its Support to the Very First Conference in ‘New Frontiers in High-Dimensional Probability and Statistics’
On February 23 and 24, the Institute for Information Transmission Problems of the Russian Academy of Sciences hosted the first international mini-conference entitled ‘New frontiers in high-dimensional probability and statistics’. The event was attended by Russian and international researchers in the field of statistical methods of analysis of multidimensional data and modern stochastic algorithms. The conference was hosted by HSE, the Institute for Information Transmission Problems of the RAS and Skoltech. Organisers included HSE Faculty of Computer Science staff, Vladimir Spokoiny, Alexey Naumov, Denis Belomestny and Quentin Paris.
In 2018, the Higher School of Economics will launch an English-taught double degree programme in partnership with the University of London in Applied Data Analysis. Graduates will be awarded an undergraduate degree from HSE in Applied Mathematics and Information Science and a Bachelor of Science in Data Science and Business Analytics from the University of London. International applicants are invited to apply online starting November 15, 2017.
‘Our Programme Aims to Make a Research Breakthrough at the Intersection of Mathematics and Computer Science’
In 2017, the HSE Faculty of Computer Science and Skoltech are opening admissions to the Master’s programme inStatistical Learning Theory, which will become the successor to theMathematical Methods of Optimization and Stochastics programme.Vladimir Spokoiny, the programme’s academic supervisor and professor of mathematics at Humboldt University in Berlin, told us about the research part of the new programme and the opportunities it offers to both Master’s students and undergraduate students alike.
The 39th interdisciplinary school and conference ‘Information Technology and Systems 2015’ (ITaS 2015), organized by the Kharkevich Institute for Information Transmission Problems (IITP RAS) with the participation of HSE, took place in Sochi from September 7–11, 2015.