Elena Kantonistova
- Associate Professor:Faculty of Computer Science / Big Data and Information Retrieval School
- Programme Academic Supervisor:Artificial Intelligence
- Elena Kantonistova has been at HSE University since 2017.
Education and Degrees
- 2016
Candidate of Sciences* (PhD)
- 2012
Degree in Mathematics
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.
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)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Machine Learning: Basic Concepts (Minor; 3, 4 module)Rus
- Mentor's Seminar (Master’s programme; Faculty of Computer Science; 2 year, 1-3 module)Rus
- Mentor's Seminar (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Rus
- Preparation for Data Scientist and Machine Learning Engineer Interview (Mago-Lego; 3 module)Rus
- Seminar "Additional Machine Learning Chapters" (Master’s programme; Faculty of Computer Science; 2 year, 1 module)Rus
- Past Courses
Courses (2022/2023)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Interview preparation for Data Scientist and Machine Learning Engineer positions (Master’s programme; Faculty of Computer Science; 2 year, 2 module)Rus
- Introduction to Deep Learning (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Key Seminar: Machine Learning (Master’s programme; Faculty of Computer Science; 1 year, 2, 3 module)Rus
Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; field of study "38.03.01. Экономика", field of study "38.03.01. Экономика"; 4 year, 1, 2 module)Rus
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1, 2 module)Rus
- Machine Learning (Optional course (faculty); 3, 4 module)Rus
- Machine Learning: Basic Concepts (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Mathematics for Data Analysis (Master’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Rus
- Mentor's Seminar (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Rus
- Project Seminar "Collection and processing of Big Data" (Master’s programme; Faculty of Computer Science; 2 year, 3 module)Rus
- Research Seminar "Applied problems of data analysis" (Master’s programme; Faculty of Computer Science; 2 year, 1 module)Rus
Courses (2021/2022)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Applied Statistical Data Analysis (Master’s programme; Faculty of Computer Science; 1 year, 4 module)Rus
- Calculus 2 (Bachelor’s programme; Faculty of Computer Science; 2 year, 1-4 module)Rus
- Introduction to Deep Learning (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Introduction to Deep Learning (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-3 module)Eng
Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; field of study "38.03.01. Экономика", field of study "38.03.01. Экономика"; 3 year, 1, 2 module)Rus
Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; field of study "38.03.01. Экономика", field of study "38.03.01. Экономика"; 4 year, 1, 2 module)Rus
- Machine Learning: Basic Concepts (Minor; Faculty of Computer Science; 3, 4 module)Rus
Courses (2020/2021)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Data Analysis and Visualization (Bachelor’s programme; School of Foreign Languages; 2 year, 1, 2 module)Rus
- Introduction to Data Analysis (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Introduction to Deep Learning (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-3 module)Eng
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; 4 year, 1, 2 module)Rus
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1, 2 module)Rus
Courses (2019/2020)
Introduction to Data Analysis (Bachelor’s programme; Faculty of World Economy and International Affairs; field of study "41.03.06. Публичная политика и социальные науки", field of study "41.03.05. Международные отношения"; 1 year, 2 module)Eng
Courses (2018/2019)
- Data Analysis and Visualization (Bachelor’s programme; School of Foreign Languages; 2 year, 3, 4 module)Rus
- Data Culture and Statistics (Bachelor’s programme; Faculty of World Economy and International Affairs; 1 year, 2 module)Eng
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1, 2 module)Rus
Courses (2017/2018)
Introduction to Data Culture (Bachelor’s programme; Faculty of World Economy and International Affairs; 1 year, 3, 4 module)Eng
Publications9
- Article Кантонистова Е. О., Родионов И. В. О критериях проверки гипотезы об эквивалентности хвостов распределений // Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика). 2022. Т. 507. № 1. С. 36-39. doi
- Article Кантонистова Е. О., Родионов И. В. О критериях различения хвостов распределений, инвариантных относительно параметра масштаба // Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика). 2022. Т. 503. № 1. С. 54-58. doi
- Article Kantonistova E., Rodionov I. Analogues of Classical Goodness-of-Fit Tests for Distribution Tails / Пер. с рус. // Doklady Mathematics (Российская Федерация). 2021. Vol. 103. No. 1. P. 35-38. doi
- Article Кантонистова Е. О., Родионов И. В. Об аналогах классических критериев согласия для хвостов распределений // Доклады Российской академии наук. Математика, информатика, процессы управления, Россия. 2021. Т. 496. № 1. С. 44-47. doi
- Article Кантонистова Е. О. Топологическая классификация интегрируемых гамильтоновых систем на поверхностях вращения в потенциальном поле // Математический сборник. 2016. Т. 207. № 3. С. 47-92.
- Book Kantonistova E., Фоменко А. Т. Continuous and Distributed Systems II. Theory and Applications Vol. 30: Topological Classification of Geodesic Flows on Revolution 2-Surfaces with Potential. Springer, 2015.
- Article Кантонистова Е. О. Лиувиллева классификация интегрируемых гамильтоновых систем на поверхностях вращения // Вестник Московского университета. Серия 1: Математика. Механика. 2015. № 5. С. 41-44.
- Article Кантонистова Е. О. Целочисленные решетки переменных действия для системы "сферический маятник" // Вестник Московского университета. Серия 1: Математика. Механика. 2014. № 4. С. 6-17.
- Article Кантонистова Е. О. Целочисленные решетки переменных действие для обобщенного случая Лагранжа // Вестник Московского университета. Серия 1: Математика. Механика. 2012. № 1. С. 54-58.
HSE University Faculty of Computer Science Holds Meetup on Data Science in Yerevan
In late April, the HSE University Faculty of Computer Science organised its first data science meetup in the capital of Armenia together with the Russian-Armenian University (RAU). The event featured speakers from HSE University, Yandex, and SberDevices. The meeting featured the participation of students from Yerevan universities who have recently become acquainted with data science, as well as specialists in the field.