Dmitrii Kiselev
- Junior Research Fellow:Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
- Junior Research Fellow:Faculty of Computer Science / Laboratory for Models and Methods of Computational Pragmatics
- Dmitrii Kiselev has been at HSE University since 2019.
Courses (2022/2023)
- Data Science for Business (Mago-Lego; 4 module)Eng
Network Science (Master’s programme; Faculty of Computer Science; field of study "01.04.02. Прикладная математика и информатика", field of study "01.04.02. Прикладная математика и информатика"; 1 year, 3, 4 module)Rus
- Structural Analysis and Visualization of Networks (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Past Courses
Courses (2019/2020)
Introduction to Network Analysis (Bachelor’s programme; Faculty of Social Sciences; 4 year, 2 module)Rus
Dissertation for a degree of Candidate of Science
2023
D. Kiselev Graph-based recommender systems using network embeddings
Publications7
- Article Li X., Makarov I., Kiselev D. Predicting Molecule Toxicity via Descriptor-based Graph Self-supervised Learning // IEEE Access. 2023. Vol. 11. P. 91842-91849. doi
- Article Kiselev D., Makarov I. Exploration in Sequential Recommender Systems via Graph Representations // IEEE Access. 2022. Vol. 10. P. 123614-123621. doi
- Article Makarov I., Savchenko A., Arseny Korovko, Leonid Sherstyuk, Severin N., Kiselev D., Mikheev Aleksandr, Babaev D. Temporal network embedding framework with causal anonymous walks representations // PeerJ Computer Science. 2022. Vol. 8. Article e858. doi
- Article Makarov I., Makarov M., Kiselev D. Fusion of text and graph information for machine learning problems on networks // PeerJ Computer Science. 2021. Vol. 7. Article e526. doi
- Article Makarov I., Korovina K., Kiselev D. JONNEE: Joint Network Nodes and Edges Embedding // IEEE Access. 2021. Vol. 9. P. 144646-144659. doi
- Article Makarov I., Kiselev D., Nikitinsky N., Subelj L. Survey on graph embeddings and their applications to machine learning problems on graphs // PeerJ Computer Science. 2021. Vol. 7. P. 1-62. doi
- Chapter Kiselev D., Makarov I. Prediction of New Itinerary Markets for Airlines via Network Embedding, 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. 315-325. doi
Employment history
2020 г. - Laboratory for Models and Methods of Computational Pragmatics (junior researc fellow)
‘I Like to Think that the Solutions We Find Can Help People in the Future’
Innopolis University has announced the results of Global Al Challenge, an international AI industry online hackathon in which teams of developers compete to create new materials using artificial intelligence. The DrugANNs team, which included students from the HSE University Faculty of Computer Science, took third place.