Marina Ananyeva
- Senior Lecturer: Faculty of Computer Science / Big Data and Information Retrieval School / Joint Department with T-Вank
- Marina Ananyeva has been at HSE University since 2025.
- Language Proficiency
- English
- French
- Contacts
- Phone:
27331
+79998868453 - Address: 11 Pokrovsky Bulvar, Pokrovka Complex, room S812
- ORCID: 0000-0002-9885-2230
- ResearcherID: AAP-1532-2021
- Scopus AuthorID: 57195756910
- Google Scholar
- Supervisors
- D. I. Ignatov
- A. V. Chernov
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Education
HSE University
HSE University
Postgraduate study (PhD), National Research University Higher School of Economics, Graduation year 2024, Specialty "Informatics and Computer Engineering", Qualification "Researcher. Research Teacher"
Awards and Accomplishments
- Best Teacher — 2022–2023
Courses (2024/2025)
- Recommender Systems (Bachelor’s programme; Faculty of Economic Sciences field of study Applied Mathematics and Information Science, Economics; 3 year, 3, 4 module)Rus
- Recommender Systems (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
- Recommender Systems (Mago-Lego; 3, 4 module)Rus
- Recommender Systems (Master field of study Applied Mathematics and Informatics; 1 year, 3, 4 module)Rus
- Past Courses
Courses (2023/2024)
- Recommender Systems (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
Courses (2022/2023)
- Recommender Systems (Master’s programme; Faculty of Computer Science field of study Applied Mathematics and Informatics; 2 year, 1 module)Rus
- Recommender Systems (Mago-Lego; 1 module)Rus
Courses (2021/2022)
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 3 year, 1, 2 module)Rus
- Machine Learning (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 4 year, 1, 2 module)Rus
- Research Seminar (Master’s programme; Faculty of Computer Science field of study Applied Mathematics and Informatics; 2 year, 1, 2 module)Rus
Courses (2020/2021)
- Data Analysis in Economics and Finance (Bachelor’s programme; Faculty of World Economy and International Affairs field of study International Relations; 3 year, 1 module)Eng
- Data Analysis in Politics and Journalism (Bachelor’s programme; Faculty of World Economy and International Affairs field of study International Relations; 3 year, 1 module)Eng
- Data Analysis in Python (Bachelor’s programme; Faculty of World Economy and International Affairs field of study International Relations, field of study Public Policy and Social Sciences; 2 year, 2-4 module)Eng
- Data Analysis in Python (Bachelor’s programme; Faculty of Economic Sciences field of study Economics; 2 year, 1, 2 module)Rus
- Research Seminar (Master’s programme; Faculty of Computer Science field of study Applied Mathematics and Informatics; 2 year, 1, 2 module)Rus
Conferences
- 2022
16th ACM Conference on Recommender Systems (RecSys). 4th Workshop of Knowledge-aware and Conversational Recommender Systems (KaRS) (Сиэтл). Presentation: Revisiting the performance evaluation of knowledge-aware recommender systems: are we making progress?
16th ACM Conference on Recommender Systems (RecSys). 5th Workshop on Online Recommender Systems and User Modeling (ORSUM) (Сиэтл ). Presentation: Towards interaction-based user embeddings in sequential recommender models
16th ACM Conference on Recommender Systems (RecSys). 5th Workshop on Online Recommender Systems and User Modeling (ORSUM) (Сиэтл ). Presentation: Next-basket recommendation with flexible total cos
16th ACM Conference on Recommender Systems. The International Workshop on Personalization & Recommender Systems in Financial Services (FinRec) (Сиэтл). Presentation: Personal merchant recommendations in online banking
Recommender Systems: New Algorithms and Current Practices
The AI and Digital Science Institute at the HSE Faculty of Computer Science hosted a conference focused on cutting-edge recommender system technologies. In an atmosphere of active knowledge sharing among leading industry experts, participants were introduced to the latest advancements and practical solutions in recommender model development.