Elena I. Bolshakova

Associate Professor: Faculty of Computer Science / School of Data Analysis and Artificial Intelligence

Elena I. Bolshakova has been at HSE University since 2009.

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Education, Degrees and Academic Titles

2000

Associate Professor

1986

Candidate of Sciences* (PhD)

1980

Degree
Lomonosov Moscow State University

* Candidate of Sciences
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 (2024/2025)

Onthologies and Semantic Technologies (Master’s programme; Faculty of Humanities; 2 year, 2 module)Rus
Past Courses

Courses (2023/2024)

Computational Linguistics and Text Analysis (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Rus
Onthologies and Semantic Technologies (Master’s programme; Faculty of Humanities field of study Fundamental and Applied Linguistics, field of study Fundamental and Applied Linguistics; 2 year, 2 module)Rus
Onthologies and Semantic Technologies (Mago-Lego; 2 module)Rus

Courses (2022/2023)

Computational Linguistics and Text Analysis (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Rus
Computational Linguistics and Text Analysis (Mago-Lego; 3, 4 module)Rus
Onthologies and Semantic Technologies (Master’s programme; Faculty of Humanities; 2 year, 1, 2 module)Eng

Courses (2021/2022)

Computational Linguistics and Text Analysis (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Rus

Courses (2020/2021)

Computational Linguistics and Text Analysis (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Rus

Timetable for today

Full timetable

Conferences

2024
Ломоносовские чтения-2024 (Москва). Presentation: Пути автоматизации построения наборов данных с терминологической разметкой

2023
Тихоновские чтения-2023 (Москва). Presentation: Автоматическая оценка сложности текстов: подходы и методы

2022
Computational Linguistics and Intellectual Technologies (Москва). Presentation: Refining Criteria of Paronymy for Building Computer Dictionaries of Russian Paronyms

2021
The 10th International Conference on Analysis of Images, Social Networks and Texts (Тбилиси). Presentation: Building a Combined Morphological Model for Russian Word Forms

2013
European Conference on Information Retrieval 2013 (ECIR 2013) (Москва). Presentation: Topic Models Can Improve Domain Term Extraction.

Supervisor of the following Doctoral theses

for a Candidate of Sciences degree

1
Methods and tools of morphological segmentation for natural language processing systems, 2023

Employment history

1983-1993 - Assistant of the Department of Algorithmic Languages of the Faculty of the Moscow State University .

In 1983-90, he was a teacher of the Evening Mathematical School for Schoolchildren at the Moscow State University VMK, organizer of the first two programming Olympiads for schoolchildren at the VMK.

1993-96 - Senior lecturer at the Faculty of the Moscow State University named after M.V. Lomonosov.

from 1996 to present. Time - Associate Professor of the Department of Algorithmic Languages of the Faculty of the Moscow State University.

1997-99, 2002-2012 - Senior Researcher (part-time) of the Faculty of Philology of Lomonosov Moscow State University.

2000-2001 - Research Professor at the Computer Research Center of the National Polytechnic Institute, Mexico City.

From 2009-present - Associate Professor at School of Analysis and Artificial Intelligence

Aug

2017

Summer School on Profession of Future – Data Analysis

From July 24th to 28th, 2017, a summer school on ‘Automatic text processing and data analysis’ took place at HSE MIEM. Thirty undergraduate, master’s and doctoral students from HSE, MIPT, MSU, Bauman State University, St. Petersburg State University, and other universities from Helsinki, Kazan, Chelyabinsk, and Yaroslavl spent their days studying machine learning and data analysis and solving problems in teams.