# Valery A. Kalyagin

- Professor, Department Head:HSE Campus in Nizhny Novgorod / Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod) / Department of Applied Mathematics and Informatics
- Laboratory Head:HSE Campus in Nizhny Novgorod / Laboratory of Algorithms and Technologies for Networks Analysis (Nizhny Novgorod)
- Programme Scientific Supervisor:Data Mining

- Tenured Professor (2009)
- Distinguished Professor (2018)

- Valery A. Kalyagin has been at HSE University since 1997.

### Education, Degrees and Academic Titles

- 1997Professor
- 1995
Doctor of Sciences* in Real, Complex and Functional Analysis

Lomonosov Moscow State University - 1992Associate Professor
- 1981
Candidate of Sciences* (PhD) in Real, Complex and Functional Analysis

- 1980
Doctoral programme

Lomonosov Moscow State University - 1974
Degree

Lobachevskiy Gorky State University

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.

### Area of expertise

mathematics, applied mathematics, computer sciences, constructive complex analysis (rational approximations), mathematical modelling, actuarial mathematics, probabilistic and statistical models

### Courses (2021/2022)

- Mathematics for computer vision (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 1 year, 1 module)Eng
- Modeling of Financial Operations (Bachelor’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 4 year, 1, 2 module)Eng
- Modern Methods of Data Analysis (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 1 year, 1, 2 module)Rus
- Research seminar "Modern Problems of Operations Research" (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 2 year, 3 module)Rus
- Past Courses

### Courses (2020/2021)

- Modeling of Financial Operations (Bachelor’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 4 year, 1, 2 module)Eng
- Modern Methods of Decision Making (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 1 year, 3, 4 module)Rus
- Research seminar "Modern Problems of Operations Research" (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 2 year, 3 module)Rus

### Courses (2019/2020)

- Applied Data Analysis Problems (Minor; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 3, 4 module)Rus
- Modeling of Financial Operations (Bachelor’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 4 year, 1 module)Eng
- Models of Network Structures (Bachelor’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 4 year, 1, 2 module)Rus
- Modern Methods of Decision Making (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 1 year, 3, 4 module)Rus
- Research seminar "Modern Problems of Operations Research" (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 2 year, 3 module)Rus

### Courses (2018/2019)

- Applied Data Analysis Problems (Minor; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 3, 4 module)Rus
- Data Analysis (Bachelor’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 2 year, 3, 4 module)Rus
- Introduction to Data Analysis (Minor; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 3, 4 module)Rus
- Modern Machine Learning Methods (Minor; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 1, 2 module)Rus
- Theory and Methods of Translation and Compilation (Bachelor’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 3 year, 1, 2 module)Rus

### Courses (2017/2018)

### Editorial board membership

2010: Member of the Editorial Board, *Бизнес-информатика* (*Business Informatics*).

### Grants

Russian Foundation for Basic Research, grant 18-07-00524 «Decision Making in Graphical Model Selection Problem», Principal Investigator.

### Participation at International Conferences, talks

**2019 **

- 18th International Conference on Mathematical Optimization Theory and Operations Research (MOTOR – 2019), Ekaterinburg, July 08-12, 2019. Invited Talk: Clustering in random variables networks http://motor2019.uran.ru/

- 20th April International Academic Conference on Economic and Social Development, Moscow, HSE, April 09-12, https://conf.hse.ru/en/2019/about Invited talk: Adaptive identification algorithm in random variable networks

- Russia Vision Forum, organized by Huawei Central Research Institute, February 21-22, 2019 Moscow, Russia. Plenary talk: Data Mining in Random Variables Network.

- Open Lecture at the Faculty of Computer Science HSE Moscow, April 08, 2019, https://cs.hse.ru/announcements/254960979.html , Invited talk: Uncertainty of decision making in random variables networks.

**2018 **

- International Forum on High-end Equipment Smart Manufacturing Engineering Management in the New Generation Information Technology Environment, Hefei University of Technology, May, 06-09, 2018, Hefei, China. Talk: Cell formation algorithms in manufacturing and applications

- International Conference on Network Analysis (NET 2018), Yandex, Moscow, May 18-19, 2018, http://nnov.hse.ru/en/latna/conferences/net2018. Talk: Loss function, unbiasedness, and optimality of Gaussian graphical model selection

- International Conference Learning and Intelligent OptimizatioN (LION 12), Kalamata, Greece, June 10-15, 2018, http://www.caopt.com/LION12. Talk: Optimality of multiple decision statistical procedure for Gaussian graphical model selection

**2017 **

- XVIII April Conference on Economic and Social Development, Moscow, HSE, April 11-14, 2017, https://www.hse.ru/news/186991819.html

Talk: Measures of similarity and network structures on stock markets

- Conference on approximation and optimization, Athens, Greece, June 29-30, 2017, http://caoaca.com

Plenary talk: Optimal Portfolio Selection and Estimation of Covariance Matrix: Bias-efficiency tradeoff

- 44th International Symposium on Operational Research - SYM-OP-IS 2017, Zlatibor, Serbia, 25-28 September 2017, http://www.symopis.vggs.rs/

Plenary talk: Market network analysis: identification of network structures in market network.

- 2d Vietnam International Applied Mathematics Conference, VIAMC 2017, Ho Shi Minh, Vietnam, December 15-18, 2017.

Plenary talk: Robust identification of network structures in stock market

**2016 **

Workshop on Critical and collective effects in graphs and networks, April 25-29 апреля, Yandex - MPTI, Moscow (http://discrete-mathematics.org/?page_id=451/). Talk: Identification of threshold graph in correlation networks.

Discrete Optimization and Operations Research, DOOR 2016, September 19-23, Vladivostok. http://math.nsc.ru/conference/door/2016/index.html.

Talk: Robust identification of subgraphs in a complete weighted graph associated with a set of random variables.

Keldysh Institute of Applied Mathematics of Russian Academy of Science,

Talk: on some problems with Big Data, April 21, 2016.

International Summer School on Operational Research and Applications, Nizhny Novgorod, May 22 – 25, 2016. https://nnov.hse.ru/en/latna/conferences/school2016.

Lecture: Network models for stock market

**2015 **

WCGO IV, World Congress on Global Optimization , February 22-25, 2015, University of Florida, USA http://www.caopt.com/WCGO/

Talk: Optimal Identification Procedures in Gaussian Graphical Models

Yandex – HSE Workshop, Applied optimization and search problems on networks (graphs)

April 06, Moscow.

Talk: Problems of identification of network structures

CMS 2015, 12th International Conference on Computational Management Science, May 27-29, University of Prague, Czech Republic http://cms2015.cuni.cz/

Talk: Robust computation of the market graph

MOD 2015, International Workshop on Machine learning, Optimization and big Data, July 21-23, 2015, Taormina, Sicily, Italy http://www.taosciences.it/mod-2015/

Tutorial: Statistical Inferences in Graphical Models

**2014 .**

XVI International Conference "Optimization methods and Applications", June 30 – July 6, 2014, Olkhon, Irkutsk, http://sei.irk.ru/conferences/mopt2014/index.html

Title of the talk: A general approach to market network analysis

International Conference “Optimization Control and Applications in the Information Age”, June 15-20, 2014, Chalkidiki, Greece, http://pardalos60.com/

Title of the talk: Market Graph and Markowitz Model

Intenational Conference “Learning and Intelligent OptimizatioN (LION 8)”, 16-21 февраля, 2014, Университет Флориды, США, http://caopt.com/LION8

Title of the talk: General Approach to Network Analysis of Statistical Data Sets

International Conference «Science of Future», St Petersburg, September 16-21, 2014. http://www.p220conf.ru/.

Title of the talk: Identification of Network Structures in Statistical Data Sets

An International Symposium on Orthogonality, Quadrature and Related Topics, Puerto de la Cruz, Tenerife, Spain. January 20-24, 2014. http://gama.uc3m.es/claroline1811/courses/CONG/document/index.html

Title of the talk: On a numerical stability of modified Chebychev algorithm for multiple orthogonal polynomials and generalized Volterra lattice

International Conference on Orthogonal Polynomials, Integrable Systems and Their Applications, Shanghai Jiao Tong University and Shaoxing University, October 25-29, 2014 (ICOPISTA-2014),

http://math.sjtu.edu.cn/conference/icopista/index.html

Title of the talk: Discrete KP equation, generalized Volterra lattice and multiple orthogonal polynomials

International Conference “Complex Analysis and Related Topics”, St Petersburg, April 14-18, 2014, http://en.chebyshev.spb.ru/analysis_conference/

Title of the talk: Asymptotics of sharp constants in Markov-Bernstein inequalities

### 2020^{4}

- Book
*Mathematical Optimization Theory and Operations Research, 19th International Conference, MOTOR 2020, Novosibirsk, Russia, July 6–10, 2020, (Т. 12095)*/ Ed. by A. Kononov, M. Khachay, P. Pardalos, V. A. Kalyagin. Cham : Springer, 2020. doi - Article Granata I., Guarracino M. R., Kalyagin V. A., Maddalena L., Manipur I., Pardalos P. M. Model simplification for supervised classification of metabolic networks //
*Annals of Mathematics and Artificial Intelligence*. 2020. Vol. 88. P. 91-104. doi - Book
*Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics*/ Ed. by I. S. Bychkov, V. A. Kalyagin, P. M. Pardalos, O. Prokopyev. Vol. 315. Springer, 2020. doi - Chapter Kalyagin V. A., Slashchinin S. Uncertainty of Efficient Frontier in Portfolio Optimization, in:
*Lecture Notes in Computer Science, Learning and Intelligent Optimization, 14th International Conference on Learning and Intelligent Optimization (LION 2020)*Vol. 12096: 14th International Conference, LION 14, Athens, Greece, May 24–28, 2020, Revised Selected Papers. Switzerland : Springer, 2020. doi P. 371-376. doi

### 2019^{3}

- Article Kalyagin V. A., Slashchinin S. Impact of error in parameter estimations on large scale portfolio optimization //
*Springer Optimization and Its Applications*. 2019. Vol. 145. P. 151-184. doi - Article Kalyagin V. A., Koldanov A. P., Koldanov P., Pardalos P. M. Loss function, unbiasedness, and optimality of Gaussian graphical model selection //
*Journal of Statistical Planning and Inference*. 2019. Vol. 201. P. 32-39. doi - Article Kalyagin V. A., Koldanov A. P., Koldanov P., Pardalos P. M. Optimality of Multiple Decision Statistical Procedure for Gaussian Graphical Model Selection //
*Lecture Notes in Computer Science*. 2019. No. 11353. P. 304-308. doi

### 2018^{4}

- Chapter Grechikhin I., Kalyagin V. A. Comparison of statistical procedures for Gaussian graphical model selection, in:
*Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics*Vol. 247. Springer, 2018. doi P. 269-279. doi - Book Valery A. Kalyagin, Panos M. Pardalos, Oleg Prokopyev, Irina Utkina.
*Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics*Vol. 247. Springer, 2018. doi - Article Kalyagin V. A., Koldanov A. P., Koldanov P., Pardalos P. M. Optimal decision for the market graph identification problem in a sign similarity network //
*Annals of Operations Research*. 2018. Vol. 266. No. 1-2. P. 313-327. doi - Chapter Granata I., Guarracino M. R., Kalyagin V. A., Maddalena L., Manipur I., Pardalos P. M. Supervised Classification of Metabolic Networks, in:
*Proceedings 2018 IEEE International Conference on Bioinformatics and Biomedicine*. Madrid : IEEE, 2018. P. 2688-2693. doi

### 2017^{5}

- Book
*Models, Algorithms, and Technologies for Network Analysis. Springer Proceedings in Mathematics & Statistics*/ Ed. by V. A. Kalyagin, A. I. Nikolaev, P. M. Pardalos, O. Prokopyev. Vol. 197. Springer, 2017. doi - Article Pardalos P. M., Kalyagin V. A. Preface //
*Optimization Methods and Software*. 2017. Vol. 32. No. 2. P. 221-221. doi - Article Pardalos P. M., Kalyagin V. A. Preface to the special issue on “Clustering and search techniques in large scale networks” //
*Optimization Letters*. 2017. Vol. 11. No. 2. P. 247-247. doi - Article Kalyagin V. A., Koldanov A. P., Petr A. Koldanov. Robust identification in random variables networks //
*Journal of Statistical Planning and Inference*. 2017. Vol. 181. No. Feb . P. 30-40. doi - Article Koldanov P., Koldanov A. P., Kalyagin V. A., Pardalos P. M. Uniformly most powerful unbiased test for conditional independence in Gaussian graphical model //
*Statistics and Probability Letters*. 2017. Vol. 122. P. 90-95. doi

### 2016^{4}

- Book
*Models, Algorithms and Technologies for Network Analysis, Springer Proceedings in Mathematics & Statistics*/ Ed. by V. A. Kalyagin, Petr A. Koldanov, P. M. Pardalos. Vol. 156. Switzerland : Springer, 2016. doi - Article Kalyagin V. A., Koldanov A. P., Pardalos P. On multivariate network analysis of statistical data sets with different measures of association //
*Annals of Mathematics and Artificial Intelligence*. 2016. Vol. 76. No. 1. P. 83-92. doi - Article Koldanov P., Kalyagin V. A., Bautin G. A. On some statistical procedures for stock selection problem //
*Annals of Mathematics and Artificial Intelligence*. 2016. Vol. 76. No. 1. P. 47-57. doi - Chapter Kazakov M., Kalyagin V. A. Spectral Properties of Financial Correlation Matrices, in:
*Models, Algorithms and Technologies for Network Analysis, Springer Proceedings in Mathematics & Statistics*/ Ed. by V. A. Kalyagin, Petr A. Koldanov, P. M. Pardalos. Vol. 156. Switzerland : Springer, 2016. doi P. 135-156. doi

### 2015^{3}

- Preprint Batsyn M.V., Kalyagin V.A., Tulyakov D.
*An efficient approach to the protein structure alignment problem*/ Институт прикладной математики им. М.В. Келдыша Российской академии наук. 2015. No. 91. - Article Aptekarev A., Draux A., Kalyagin V. A., Tulyakov D. Asymptotics of sharp constants of markov-bernstein inequalities in integral norm with jacobi weight //
*Proceedings of the American Mathematical Society*. 2015. Vol. 143. No. 9. P. 3847-3862. doi - Article Koldanov A. P., Kalyagin V. A., Pardalos P. M. Step Down and Step Up Statistical Procedures for Stock Selection with Sharp Ratio //
*Lecture Notes in Computer Science*. 2015. Vol. 9432. P. 26-36.

### 2014^{6}

- Chapter Kalyagin V. A., Koldanov A. P., Pardalos P. M. A General Approach to Network Analysis of Statistical Data Sets, in:
*Learning and Intelligent Optimization.*/ Ed. by P. M. Pardalos, M. Resende, C. Vogiatzis, J. Walteros. Vol. 8426: Lectute Notes in Computer Science. Switzerland : Springer, 2014. P. 88-97. - Chapter Koldanov P., Kalyagin V. A., Koldanov A. P., Zamaraev V. A. Market Graph and Markowitz Model, in:
*Optimization oi Science and Engineering (In Honor of the 60th Birthday of Panos M. Pardalos)*. NY : Springer, 2014. Ch. 15. P. 301-313. doi - Article Kalyagin V.A., Koldanov A.P., Koldanov P.A., Pardalos P.M., Zamaraev V.A. Measures of uncertainty in market network analysis //
*Physica A: Statistical Mechanics and its Applications*. 2014. Vol. 413. No. 1. P. 59-70. doi - Book Kalyagin V. A., Pardalos P. M., Rassias T.
*Network Models in Economics and Finance*. Springer, 2014. - Article Kalyagin V. A., Koldanov P., Zamaraev V. A. Network Structure Ucertainty for Different Markets //
*Springer Optimization and Its Applications*. 2014. Vol. 100. P. 181-197. - Article Vizgunov Arsenii, Goldengorin B., Kalyagin V. A., Koldanov A. P., Koldanov P.A., Pardalos P. M. Network approach for the Russian stock market //
*Computational Management Science*. 2014. Vol. 11. No. 1-2. P. 45-55. doi

### 2013^{7}

- Chapter Mikhail Batsyn, Valery Kalyagin. An Analytical Expression for the Distribution of the Sum of Random Variables with Mixed Uniform Density and Mass Function, in:
*Models, Algorithms, and Technologies for Network Analysis*/ Ed. by B. I. Goldengorin, V. A. Kalyagin, P. M. Pardalos. Issue 32. NY : Springer, 2013. Ch. 3. P. 51-63. - Article Bautin G., Kalyagin V. A., Koldanov A. P. Comparative Analysis of Two Similarity Measures for the Market Graph Construction //
*Springer Proceedings in Mathematics & Statistics*. 2013. Vol. 59. P. 29-41. - Article Beckermann B., Kalyagin V., Matos A., Wielonsky F. Equilibrium Problems for Vector Potentials with Semidefinite Interaction Matrices and Constrained Masses //
*Constructive Approximation*. 2013. Vol. 37. No. 1. P. 101-134. doi - Book
*Models, Algorithms, and Technologies for Network Analysis*/ Ed. by B. I. Goldengorin, V. A. Kalyagin, P. M. Pardalos. Issue 32. NY : Springer, 2013. (in press) - Book
*Models, Algorithms, and Technologies for Network Analysis*/ Ed. by Boris I. Goldengorin, Valery A. Kalyagin, Panos M. Pardalos. Vol. 59. NY : Springer, 2013. - Article Kalyagin V. A., Koldanov A. P., Koldanov P.A., Pardalos P. M., Bautin G. A. Simple measure of similarity for the market graph construction //
*Computational Management Science*. 2013. Vol. 10. No. 2-3. P. 105-124. doi - Article Koldanov A. P., Kalyagin V. A., Koldanov P.A., Pardalos P. M. Statistical procedures for the market graph construction //
*Computational Statistics & Data Analysis*. 2013. Vol. 68. P. 17-29.

### 2012^{1}

*Financial Decision Making Using Computational Intelligence*/ Ed. by M. Doumpos, C. Zopounidis, P. M. Pardalos. Issue 70. L., NY, Dordrecht, Heidelberg : Springer, 2012. P. 233-251.

### 2011^{2}

- Article Beckermann B., Matos A., Wielonsky F., Kalyagin V. A. How well does the Hermite-Padé approximation smooth the Gibbs phenomenon? //
*Mathematics of Computation*. 2011. Vol. 80. No. 274. P. 931-958. doi - Article Batsyn M. V., Kalyagin V. A. Power Index Axiomatics in the Problem of Voting with Quota / Пер. с рус. //
*Automation and Remote Control*. 2011. Vol. 72. No. 3. P. 600-614.

### 2010^{4}

- Chapter Batsyn M. V., Kalyagin V. A. Default risk estimation in reinsurance contracts on the base of simulation model, in:
*History of accounting, buisness administration doctrines and development of new methods of management in Italy and Russia, 2010*/ Ed. by S. Terzani, O. Kozyrev. Milan : Rirea, 2010. P. 8-20. - Article Aleskerov F. T., Chistyakov V., Kaliaguine V. A. Social threshold aggregations //
*Social Choice and Welfare*. 2010. Vol. 35. No. 4. P. 627-646. doi - Article Aleskerov F., Chistyakov V.V., Kalyagin V. The threshold aggregation //
*Economics Letters*. 2010. Vol. 107. No. 2. P. 261-262. doi - Preprint Aleskerov F. T., Чистяков В. В., Kalyagin V. A.
*Многокритериальные пороговые алгоритмы принятия решений*/ NRU Higher School of Economics. Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2010. No. 02.

### 2009^{3}

- Article Kaliaguine V. A., Tulyakov D., Aptekarev A. I., Lysov V. Equilibrium of vector potentials and uniformization of the algebraic curves of genus 0 //
*Journal of Computational and Applied Mathematics*. 2009. Vol. 233. No. 3. P. 602-616. doi - Article Kalyagin V. A., Saff E., Aptekarev A. I. Higher Order Three-Term Recurrences and Asymptotics of Multiple Orthogonal Polynomials //
*Constructive Approximation*. 2009. Vol. 30. No. 2. P. 175-223. doi - Article Kononova A., Kalyagin V. A. On Compact Perturbation of the Limit-Periodic Jacobi Operator //
*Mathematical notes*. 2009. Vol. 86. No. 6. P. 789-800.

### 2008^{3}

- Article Chistyakov V., Kalyagin V. A. A model of noncompensatory aggregstion with an arbitrary collections of grades //
*Доклады Академии наук*. 2008. Vol. 78. No. 1. P. 617-620. - Article Aleskerov F. T., Роgоrеlskiу К., Kalyagin V. A. Actual voting power of the IMF members based on their political-economic intergration //
*Mathematical and Computer Modelling*. 2008. Vol. 48. P. 1554-1559. - Article Роgоrеlskiу К., Kalyagin V. A., Aleskerov F. T. Power distribution analysis in the International Monetary Fund //
*Automation and Remote Control*. 2008. No. 11. P. 1946-1952. doi

### 2000^{2}

- Article Aptekarev A. I., Kalyagin V. A., Van Iseghem J. Geneticsum representation for the moments of the Stieltjes function and their application //
*Constructive Approximation*. 2000. Vol. 16. P. 487-454. - Article Draux A., Kalyagin V. A., Aptekarev A. I. On asymptotics of exact constants in the Markov-Bernstein inequalities in the weighted spaces of integrable functions with classical weight //
*Russian Mathematical Surveys*. 2000. Vol. 55. No. 1. P. 173-174.

### 1997^{2}

- Article Beckermann B., Kalyagin V. A. Diagonal of the Pade table and the approxiamation of the Weyl function of second order difference operator //
*Constructive Approximation*. 1997. Vol. 13. P. 481-510. - Article Kalyagin V. A. On a classical system of polynomials of simultaneous orthogonality //
*Journal of Computational and Applied Mathematics*. 1997. Vol. 67. P. 207-216.

### 1995^{2}

- Article Aptekarev A. I., Kalyagin V. A., van Assche W. Criterion of the resolvent set of a non-symmetric tridiagonal operators //
*Proceedings of the American Mathematical Society*. 1995. Vol. 123. No. 8. P. 2423-2430. - Article Kalyagin V. A. Note on asymptotics of ortogonal polynomials on an arc //
*Journal of Approximation Theory*. 1995. Vol. 80. P. 138-145.

## On April 7-8, within the framework of the Yasin (April) Conference, the section "Network Analysis" was held

On April 5-22, 2022, the XXII Yasin (April) International Academic Conference on Economic and Social Development organized by NRU HSE takes place. Within the conference framework, the International Laboratory for Applied Network Research traditionally organized a section, "Network Analysis," addressed to various theoretical and empirical studies from different disciplines, based on applying theoretical and methodological approaches from the field of network analysis.

## HSE University-Nizhny Novgorod to Launch Online Master of Computer Vision Programme

This year, HSE University in Nizhny Novgorod will launch its Master of Computer Vision programme on Coursera. The fully online programme has been developed by leading experts from Huawei, ItSeez3D, Intel, Harman, and Xperience AI. It will be taught in English and is open to applicants from all countries. The closing date for applications is August 16, 2021.

## HSE University-Nizhny Novgorod to Launch Online Master of Computer Vision Programme

This year, HSE University in Nizhny Novgorod will launch its Master of Computer Vision programme on Coursera. The fully online programme has been developed by leading experts from Huawei, ItSeez3D, Intel, Harman, and Xperience AI. It will be taught in English and is open to applicants from all countries. The closing date for applications is August 16, 2021.

## A Strong Profile in IT and Humanities

The HSE Look talked to Anna Blyakhman, Deputy Director of HSE Nizhny Novgorod and Associate Professor at the Faculty of Management, about the educational programmes offered at the campus and its international students.

## Developing New Research Tools

The Laboratory of Algorithms and Technologies for Networks Analysis (LATNA) in Nizhny Novgorod is one of HSE’s international laboratories. It is co-supervised by Panos Pardalos, Distinguished Professor at the University of Florida, and Valery Kalyagin, Professor and Department Head at the Department of Applied Mathematics and Informatics. Professor Kalyagin told The HSE Lookabout the lab’s research projects, its work with students, and engagement in the educational life of the campus and HSE at large.

## HSE Staff Members Awarded Status of Tenured Professor

On June 22, several HSE lecturers and staff members were awarded the status of Tenured Professor at a meeting of HSE Academic Council. Sixteen HSE staff members became Distinguished Professors at the Higher School of Economics for the first time.

## A Good Education is the Best Investment for the Future

Kirill Pogorelskiy, Assistant Professor at the Faculty of Economics, Warwick University, UK, starting August 2015. Completed his Master's in Applied Mathematics and Information Technology, specialising in Mathematical Modelling in 2009 and began a PhD in Social Sciences at Caltech, USA, which he finished this year. In an interview Kirill talked about teaching at HSE, his academic interests and doing a PhD at a top American university.

## Laboratory of Algorithms and Technologies for Networks Analysis

Panos Pardalos, Scientific Advisor of the Laboratory of Algorithms and Technologies for Networks Analysis (LATNA), and Valery Kalyagin, Head of the LATNA, talk about research projects of the laboratory.

**Laboratory of Algorithms and Technologies for Networks Analysis**

Panos Pardalos, Scientific Advisor of the Laboratory of Algorithms and Technologies for Networks Analysis (LATNA), and Valery Kalyagin, Head of the LATNA, talk about research projects of the laboratory.

## Internet Search Possible without Search Engines

Specialists from the HSE’s Nizhny Novgorod campus plan to create a new system of structuring data and accounting of webpages. The Laboratory of Algorithms and Technologies for Networks Analysis has won a grant from the Russian Science Foundation to study ‘Clustering and Search Techniques in Large Scale Networks.’