Tamara Voznesenskaya
- First Deputy Dean:Faculty of Computer Science
- Associate Professor:Faculty of Computer Science / Big Data and Information Retrieval School
- Programme Academic Supervisor: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.
Courses (2023/2024)
- Introduction to Programming (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Python Programming (Bachelor’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Eng
- Past Courses
Courses (2022/2023)
- Introduction to Programming (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Introduction to Programming (Bachelor’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
Courses (2021/2022)
- Introduction to Programming (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Introduction to Programming (Bachelor’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
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
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 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
Publications17
- Chapter Samonenko I., Voznesenskaya T., Yavorskiy R. How the Minimal Degree of a Social Graph Affects the Efficiency of an Organization, in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary Proceedings / Ed. by W. M. van der Aalst, V. Batagelj, A. V. Buzmakov, D. I. Ignatov, A. A. Kalenkova, M. Khachay, O. Koltsova, A. Kutuzov, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch, I. Makarov, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Springer, 2021. doi P. 173-181. 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, 2021. P. 130-141. doi
- 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
- 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.
HSE Faculty of Computer Science Celebrates its First Graduates of the Data Science and Business Analytics Programme
At the beginning of July, the Data Science and Business Analytics programme at the HSE Faculty of Computer Science held its first graduation ceremony. Most graduates have already found jobs in various fields—Data Science, development, product management, systems analysis, and so on. Many of the bachelors plan to continue their studies at the best international and Russian universities, but they are not going to say goodbye. ‘We have been and will always be one big team,’ they say.
Bachelor's Programme in Data Science and Business Analytics Accredited by AI Alliance Russia
The ‘Data Science and Business Analytics’ bachelor’s programme at HSE Faculty of Computer Science has received professional and public accreditation by the AI Alliance Russia. This is the third programme of the faculty that has received accreditation from the AI Alliance Russia, following the bachelor's programme in ‘Applied Mathematics and Information Science’ and the master’s programme in ‘Financial Technologies and Data Analysis’.
Students of HSE Double-Degree Programmes Top London Exams Again
The results of exams organized by the University of London (UoL) and the London School of Economics (LSE, a constituent college of UoL) have been announced. Students of HSE ICEF, the HSE Faculty of World Economy and International Relations (WEIA) and the HSE Faculty of Computer Science (FCS) have achieved the highest grades in a variety of subjects and confirmed their reputation as the top representatives of international programmes. Fourteen HSE students received awards for their academic achievements.
London School of Economics Laudes Best Double Degree Programme Students
Students of the Data Science and Business analytics double degree programme receive awards and letters of commendation for their academic achievements.
Winners of the International Data Analysis Olympiad (IDAO) Announced
The Faculty of Computer Science at HSE University, Yandex, and this year’s platinum partner, Otkritie Bank, held the International Data Analysis Olympiad (IDAO) for the fourth time. This year’s first-place winner was the ‘random team’, Ilya Kornakov and Kirill Borozdin, from Switzerland. Second and third places went to the Russian teams ‘Mylene Farmer’ (Vasiliy Rubtsov, Anvar Kurmukov) and ‘Shizika’ (Dmitry Simakov, Nikita Churkin).
"There are a lot of smart people at HSE University"
We talked to the student of the "Data Science and Business Analytics" double degree programme Yunying Pei about her projects, awards, and the LSE summer school.
International Data Analysis Olympiad IDAO-2021 Has Started
The registration period for the International Data Analysis Olympiad (IDAO-2021) is open until March 12. The qualifying round has already begun and will run until March 31. This year, the HSE Faculty of Computer Science and Yandex are holding the Olympiad for the fourth time. This year's Platinum Partner is Otkritie Bank. The Olympiad is organised by leading data analysts for their future colleagues—early career analysts and scientists.
‘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.