Tamara Voznesenskaya
- First Deputy Dean:Faculty of Computer Science
- Associate Professor:Faculty of Computer Science / Big Data and Information Retrieval School
- Programme Academic Supervisor:HSE University and University of London Double Degree Programme in Data Science and Business Analytics
- Member of the HSE Academic Council
- Tamara Voznesenskaya has been at HSE University since 2014.
Education and Degrees
- 2001
Candidate of Sciences* (PhD) in Mathematical Support and Software in Computers, Complexes and Computer Networks
Lomonosov Moscow State University
Thesis Title: Effectiveness Analysis of Synchronization Algorithms for Distributed Simulation - 1994
Degree in Applied mathematic
Lomonosov Moscow State University, Computer Science
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.
Student Term / Thesis Papers
- Bachelor
A. Fironov, Using Computer-Based Word Processing Methods to Analyze the Quality of Bug Reports. Faculty of Computer Science, 2020
D. Eremin, Automatic Russian Language Parser. Faculty of Computer Science, 2017
Я. Де Ротшильд, Feature Selection in Credit Scorecard Modelling. Faculty of Computer Science, 2017
V. Khodyreva, Prediction of Client's Response Based on Machine Learning Techniques. Faculty of Computer Science, 2017
A. Konshina, Credit Risk Model Based on Machine Learning Techniques. Faculty of Computer Science, 2017
E. Bazikova, Credit Risk Model Based on Machine Learning Techniques. Faculty of Computer Science, 2016
A. Dushatskiy, Using Machine Learning Techniques for Trading Agent Modeling. Faculty of Computer Science, 2016
- Master
I. Gorshkov, Segmentation and ЗD Reconstruction of MRI Images for Improving Vein Diseases Diagnostic. Faculty of Computer Science, 2020
Courses (2020/2021)
- Introduction into Python (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1, 2 module)Rus
- Introduction into Python (Bachelor’s programme; Faculty of Economic Sciences; 2 year, 1, 2 module)Rus
- Introduction to Programming (Bachelor’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Introduction to Programming (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Past Courses
Courses (2019/2020)
- Introduction into Python (Bachelor’s programme; Faculty of Economic Sciences; 4 year, 2 module)Rus
- Introduction into Python (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 2 module)Rus
- Introduction into Python (Bachelor’s programme; Faculty of Economic Sciences; 2 year, 2 module)Rus
- Introduction into Python (Optional course (faculty); HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE); 2 module)Rus
- Introduction to Programming (Bachelor’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Eng
- Introduction to Programming (Minor; Faculty of Computer Science; 1, 2 module)Rus
Courses (2015/2016)
- Introduction to Programming (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Introduction to VBA (Bachelor’s programme; Faculty of Economic Sciences; 2 year, 4 module)Rus
Publications16
- Chapter Samonenko I., Voznesenskaya T., Yavorskiy R. Effect of Social Graph Structure on the Utilization Rate in a Flat Organization, in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science Vol. 1086. Springer, 2020. doi P. 214-224. doi
- Chapter Samonenko I., Voznesenskaya T. The influence of self-organizing teams on the structure of the social graph, in: Tools and Methods of Program Analysis: 5th International Conference, TMPA 2019, Tbilisi, Georgia , November 7-9, 2019, Revised Selected Papers. Springer, 2019. P. 1-12.
- Article Вознесенская Т. В., Краснов Ф. В., Яворский Р. Э., Чеснокова П. В. Моделирование самоорганизующихся команд в научной среде. // Бизнес-информатика. 2019. Т. 13. № 2. С. 7-17. doi
- Chapter Yavorskiy R., Voznesenskaya T., Рудаков К. А. Visualization of Data Science Community in Russia., in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science / Ed. by W. M. van der Aalst, V. Batagelj, G. Glavaš,, D. I. Ignatov, M. Khachay, O. Koltsova, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch,, A. Napoli,, A. Savchenko, A. Panchenko,, P. M. Pardalos, M. Pelillo,. Vol. 11179. Berlin : Springer, 2018. doi Ch. 1. P. 3-9. doi
- Article Вознесенская Т. В., Леднов Д. А. Система автоматического аннотирования текстов с помощью стохастической модели // Машинное обучение и анализ данных. 2018. Т. 4. № 4. С. 266-279. doi
- Chapter Вознесенская Т. В., Деркач Д. А., Стрелков Г. М. О корреляционных функциях прямоугольного радиоимпульса с хаотической несущей в холодной плазменной среде. // В кн.: V Всероссийская Микроволновая конференция, Москва, 29 ноября - 01 декабря 2017. Доклады. М.: Институт радиотехники и электроники им. В.А.Котельникова РАН, 2017. [б.и.], 2017. С. 279 -283.
- Chapter Деркач Д. А., Вознесенская Т. В., Стрелков Г. М. Распространение прямоугольного радиоимпульса с хаотической несущей в холодной плазменной среде // В кн.: IV Всероссийская Микроволновая конференция, 23 - 25 ноября 2016 г., Москва. Доклады. М. : Институт радиотехники и электроники им. В.А. Котельникова РАН, 2016. С. 251-255.
- Article Вознесенская Т. В., Котов М. А., Леднов Д. А. Гибридный детектор речи. // Цифровая обработка сигналов. 2014. № 4. С. 54-58.
- Article Вознесенская Т. В., Леднов Д. А. Краткий обзор приложения метода условных случайных полей в области распознавания речи // Речевые технологии. 2013. № 4. С. 127-134.
- Chapter Вознесенская Т. В., Костенко В. А., Маркин М. И. Задача и алгоритм календарного планирования работ сервисного подразделения IT-компании // В кн.: Труды V Международной конференции "Дискретные модели в теории управляющих систем". Издательский отдел ф-та ВМиК МГУ им. М.В. Ломоносова, 2003.
- Article Вознесенская Т. В. Математическая модель для анализа производительности распределенных систем имитационного моделирования // Искусственный интеллект. 2002. № 2. С. 74-78.
- Article Вознесенская Т. В. Анализ алгоритмов синхронизации времени для распределенного имитационного моделирования // Искусственный интеллект. 2000. № 2. С. 24-30.
- Chapter Вознесенская Т. В. Исследование эффективности методов синхронизации времени для распределенного имитационного моделирования // В кн.: Труды Всероссийской научной конференции "Высокопроизводительные вычисления и их приложения". М. : Издательство МГУ, 2000. С. 208-211.
- Chapter Вознесенская Т. В. Математическая модель алгоритмов синхронизации времени для распределенного имитационного моделирования // В кн.: Программные системы и инструменты. Т. 1. М. : Издательский отдел ф-та ВМиК МГУ им. М.В. Ломоносова, 2000. С. 56-66.
- Chapter Вознесенская Т. В., Факанов А. Е. Распределенное имитационное моделирование МС-моделей на сетях рабочих станций // В кн.: Методы математического моделирования. МГУ, 1998.
- Chapter Вознесенская Т. В. Проблемы распределенного имитационного моделирования на системах с распределенной памятью // В кн.: Тезисы докладов V Всероссийской научно-технической конференции "Повышение эффективности методов и средств обработки информации". Тамбов : [б.и.], 1997.
‘Borders Between Countries Are Becoming Blurred Thanks to Online Communication’
Professor Oleg Melnikov is among the international professors invited to work remotely with HSE University’s students this academic year. He lives in California, runs the Data Science department at a company in Palo Alto, and teaches at Stanford and other universities in the United States. At HSE University he teaches a course on machine learning for the students of the Faculty of Computer Science and the International College of Economics and Finance (ICEF), as well as a university-wide optional course, ‘Machine Learning in Python’. He spoke about his work in an interview with the HSE News Service.
HSE University Faculty of Computer Science and Yandex Hold Final Round of International Data Analysis Olympiad IDAO-2020
The HSE Faculty of Computer Science (FCS) and Yandex held the Online Final of the IDAO-2020 International Data Analysis Olympiad, which took place for the third time. The task for the final round was provided by QIWI, the platinum partner of the event. Sberbank also became a competition partner.
"Worldwide Conversation on Women’s Higher Education and Equality in the Workplace"
On November 26, the HSE Faculty of Computer Science held the ‘IT Girls Night’ for the fifth time. This year the event was organized within the University of London’s campaign ‘Worldwide Conversation on Women’s Higher Education and Equality in the Workplace’. This campaign celebrates 150 years since the University of London opened up its ‘Special Examinations for Women’, the first university-level examinations offered for women in the UK. Ten years later, this step led to the University of London becoming the first institution of higher education in the UK to open up full degrees for women.
First International Data Analysis Olympiad Held in Moscow
On April 4, the winners of the First International Data Analysis Olympiad (IDAO) were announced. The event was organized by the HSE Faculty of Computer Science, Yandex, and Harbour.Space University (Barcelona) with the support of Sberbank. Magic City team from St. Petersburg took out first prize, a team from the Ukraine came second, and the Apex team from Belarus came third.
HSE and University of London: Joint BA Programme in Applied Data Analysis
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.
HSE Signed Partnership Agreement with Ghent University
Students and doctoral students of the HSE Faculty of Computer Science will have the opportunity to take part in exchange and double degree programmes.
