Evgeny Sokolov
- Deputy Head, Senior Lecturer:Faculty of Computer Science / Big Data and Information Retrieval School
- Academic Supervisor:Faculty of Computer Science / Continuing Education Centre
- Programme Academic Supervisor:Applied Mathematics and Information Science
- Evgeny Sokolov has been at HSE University since 2016.
Courses (2021/2022)
Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; field of study "01.03.02. Прикладная математика и информатика", field of study "01.03.02. Прикладная математика и информатика"; 3 year, 3, 4 module)Rus
Courses (2020/2021)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Introduction to Data Analysis (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Rus
Machine Learning 1 (Bachelor’s programme; Faculty of Economics, Management, and Business Informatics; field of study "38.03.05. Бизнес-информатика", field of study "09.03.04. Программная инженерия"; 3 year, 1, 2 module)Rus
Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; field of study "01.03.02. Прикладная математика и информатика", field of study "01.03.02. Прикладная математика и информатика"; 3 year, 3, 4 module)Rus
- Modern Machine Learning Methods (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Past Courses
Courses (2019/2020)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Introduction to Data Analysis (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Introduction to Machine Learning (Master’s programme; Faculty of Physics; 2 year, 1-3 module)Rus
- Introductory Research Seminar (Bachelor’s programme; Faculty of Computer Science; 2 year, 3 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Rus
Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; field of study "01.03.02. Прикладная математика и информатика", field of study "01.03.02. Прикладная математика и информатика"; 3 year, 3, 4 module)Rus
Courses (2018/2019)
- Introduction to Data Analysis (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Introductory Research Seminar (Bachelor’s programme; Faculty of Computer Science; 2 year, 3 module)Eng
Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; field of study "01.03.02. Прикладная математика и информатика", field of study "01.03.02. Прикладная математика и информатика"; 3 year, 3, 4 module)Rus
Student Term / Thesis Papers
- Bachelor
R. Sokolov, Exploration of Complex Environments in Reinforcement Learning. Faculty of Computer Science, 2020
A. Kulikov, Multidocument Summarization. Faculty of Computer Science, 2020
S. Nosov, Sentiment Analysis of the User's Reaction in the Vacancy Ranking Task. Faculty of Computer Science, 2020
Y. Nemirovsky, Determining a User's Behavioral Model Based on Their Purchases. Faculty of Computer Science, 2020
A. Iovleva, Detection of Stock Price Manipulation. Faculty of Computer Science, 2020
A. Panaetov, Occluded Human Instance Segmentation. Faculty of Computer Science, 2020
G. Kozhevnikov, Continuous Segmentation of Pointcloud. Faculty of Computer Science, 2020
N. Nesterov, Development of Intelligent Chatbot for Analytical Service. Faculty of Computer Science, 2020
E. Kazakov, Market Matching Engine Load Predictor. Faculty of Computer Science, 2020
M. Kobelev, Improving Word Classification with Graph Structures on Semi-Structured Documents Using Neural Networks. Faculty of Computer Science, 2020
N. Dolzhenko, Crosslingual Information Extraction. Faculty of Computer Science, 2020
N. Sverbiagin, Document Clustering Based on Text and Image Content for Improving the Automatic Creation of Structural Descriptions in the Stream Input System. Faculty of Computer Science, 2020
I. Rubachev, Evaluation of Self-supervised and Semi-supervised Learning Methods on Image Classification. Faculty of Computer Science, 2020
D. Gontar, Automatic Sentence Grammaticality Judgment. Faculty of Computer Science, 2020
V. Kukanov, Classification Models for Contextual Advertisements. Faculty of Computer Science, 2020
L. Gunchenko, Multidocument Summarization. Faculty of Computer Science, 2020
E. Alaev, Automatic Text Summarization Using Deep Learning. Graduate School of Business, 2020
A. Sokolov, Development and Application of a Physically Correct Muscular System Model for a 3d Character. Faculty of Computer Science, 2019
P. Vorobev, The Task of Transferring Facial Movements of a Person to a Three-Dimensional Model. Faculty of Computer Science, 2019
V. Biriukov, Automatic Moderation of Advertising Content. Faculty of Computer Science, 2019
A. Rogachevskaia, Interpretable Machine Learning Models. Faculty of Mathematics, 2019
A. Sinitsin, Optimal Graph Traversal with Deep Reinforcement Learning. Faculty of Mathematics, 2019
N. Bagiyan, Neural Style Transfer for Texts. HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE), 2019
T. Tabolov, Application Recommeder System Development. Faculty of Computer Science, 2019
N. Benkovich, Automated Analysis of the Business Process Using Process Mining. Faculty of Computer Science, 2018
R. Karpichev, Implementation of Denoiser. Faculty of Computer Science, 2018
R. Luchkov, Question-Answer System in the Banking Domain. Faculty of Computer Science, 2018
I. Gavrilov, Automated Analysis of the Business Process Using Process Mining. Faculty of Computer Science, 2018
E. Kovalev, Deep Learning for Sentiment Analysis of Short Texts. Faculty of Mathematics, 2018
D. Valter, Text Embeddings for Recommender Systems). Faculty of Computer Science, 2018
- Master
E. Vakhrameeva, Iterative Traffic Control Algorithm to Solve the Article Cold-Start Problem at Yandex.Zen. Faculty of Computer Science, 2020
A. Klimkin, Deep Cascaded Neural Networks for Inpainting Task on High Resolution Images. Faculty of Computer Science, 2020
T. Semenov, Deep Learning for Dialogue Systems. Faculty of Computer Science, 2019
Publications3
- Article Bedenkov A., Shpinev V., Suvorov N., Sokolov E., Riabenko E. Consolidating Russia and Eurasia antibiotic resistance data for 1992–2014 using search engine // Frontiers in Microbiology. 2016. Vol. 7. No. 294. P. 1-6. doi
- Chapter Romov P. A., Sokolov E. RecSys Challenge 2015: ensemble learning with categorical features, in: Proceedings of the 2015 International ACM Recommender Systems Challenge. NY : ACM, 2015. doi
- Chapter Sokolov E., Bogolubsky L. Topic Models Regularization and Initialization for Regression Problems, in: Proceedings of the 2015 Workshop on Topic Models: Post-Processing and Applications. NY : ACM, 2015. doi P. 21-27. doi
‘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.
‘I Found Almost All of the Materials I Needed to Prep for the Interview in the Master’s Programme Courses’
As a student of the first cohort of the HSE Master of Data Science online programme, Alexey Babenkov not only gained new knowledge but also used that knowledge to find a new job. He told HSE News Service how his online studies are organised, described the advantages of remote learning and explained which courses are especially useful.
Faculty of Computer Science First Year Student Wins Gold at International Olympiad in Informatics
Semyon Savkin, a graduate of Moscow School No. 57 and student of HSE University’s Bachelor's Programme in Applied Mathematics and Information, has won gold in theInternational Olympiad in Informatics individual all-around among school students from 87 countries. In the unofficial team race, Russia shares second place with USA and Iran.
Faculty of Computer Science Shares Experience
During the COVID-19 pandemic, the Faculty of Computer Science does not relent and starts new projects as well as maintains the old ones. This spring, the Faculty and HSE International Centre for Research and Teaching started the advanced training courses “Methods and practice of Python programming teaching” and “Basics of machine learning for university professors”.
How the Faculty of Computer Science Switched Online
From March 17, HSE University has made all classes online. Here’s how the Faculty was able to do that, as well as celebrate Faculty’s birthday, talk to prospective students, and develop a new YouTube channel.
HSE University Launches Russia’s First Online English-Taught Master's Programme
This academic year, HSE University will begin admissions to its new online Master's programme in Data Science, which will be offered on Coursera, the world’s leading online learning platform. The application deadline for admission to the programme is December 6. Courses begin in February. Upon the successful completion of the programme, students will receive a Master’s degree from HSE University, which is internationally recognized.
HSE’s Online Specialization ‘Advanced Machine Learning’ Receives Outstanding Educator Award from Coursera
HSE's English-taught online specialization, ‘Advanced Machine Learning’, which was created in partnership with Yandex, became the first course in Russia to receive the Outstanding Educator Award in the category of ‘Innovation’ from the global online platform Coursera.
HSE Launches Two New Specializations in Computer Science on Coursera
‘Introduction to Discrete Mathematics for Computer Science’ and ‘Advanced Machine Learning’ are English-language specializations, both created with the support of the top Russian IT firm Yandex, while the specialization ‘Introduction to Discrete Mathematics for Computer Science’ was developed with the involvement of the University of California at San Diego.
Faculty of Computer Science Staff Attend International Conference on Machine Learning
On August 6-11 the 34th International Conference on Machine Learning was held in Sydney, Australia. This conference is ranked A* by CORE, and is one of two leading conferences in the field of machine learning. It has been held annually since 2000, and this year, more than 1,000 participants from different countries took part.
HSE Team Made it to Imagine Cup, International Student Project Competition, Finals
An app developed by the Faculty of Computer Science student team has made it to the finals of the Imagine Cup 2017, an international student project technology competition. Together with the other two finalists from Russia, the HSE team will represent their country at the international finals in Seattle this summer, where they will compete for the $100,000 main prize.