Associate Professor, Lomonosov Moscow State University Russia
Iulii Vasilev is a Senior Mathematician at Lomonosov Moscow State University, specializing in machine learning, data mining, and survival analysis. He completed his Ph.D. ahead of schedule and has over six years of experience managing end-to-end machine learning lifecycles. He has published 18 scientific papers (8 indexed in Scopus & WoS) and participated in 12 conferences. At LMSU, he develops machine learning courses, supervises student research projects, and conducts industry training for Sber and VTB Bank employees. A winner of six scientific competitions, his research includes the development of survival analysis models and an open-source Python library for event prediction.
Publication Profile
Scholar
🎓 Education
Ph.D. in Computer Science, Lomonosov Moscow State University (completed ahead of schedule). Postdoctoral Research, Lomonosov Moscow State University. Developed new survival analysis models during Ph.D., leading to a software patent. Specialized in data mining, machine learning, and predictive modeling. IEEE Member with contributions to machine learning research and applications. Designed and taught data mining courses for banking professionals (Sber, VTB Bank)
💼 Experience
Senior Mathematician, Lomonosov Moscow State University. Postdoc Researcher, LMSU, working on data mining & survival analysis. Managed machine learning lifecycle projects for over six years. Published 18 papers, with 8 indexed in Scopus & WoS. Supervised student research projects and proctored exams at LMSU. Conducted corporate training programs in data mining & ML for Sber, VTB Bank. Led 8 industry consultancy projects and 6 ongoing research projects
🏆 Awards & Honors
Winner of 6 scientific competitions for research articles and grants. Received national and international recognition for contributions to machine learning & survival analysis. Secured funding for multiple research projects in statistical modeling & AI applications. Patent holder for an open-source survival analysis Python library. Recognized for excellence in teaching & research at LMSU. Award nominee for Young Scientist Award
🔍 Research Focus
Iulii Vasilev specializes in survival analysis, data mining, and machine learning. He developed Survivors, an open-source Python library for predicting event occurrences over time. His survival tree model addresses heterogeneous missing data, enabling robust event probability predictions. His research applies to medicine, engineering, and CRM and is now expanding to time-varying variables & competing risks. He has an h-index of 3 (Google Scholar), 2 (Scopus, WoS) and has worked on 6 major research projects. His models are used in real-world applications, bridging the gap between academic research and industry needs.
Publication Top Notes
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Title: Predicting COVID-19-induced lung damage based on machine learning methods
Year: 2022
Authors: I.A. Vasilev, M.I. Petrovskiy, I.V. Mashechkin, L.L. Pankratyeva
Journal: Programming and Computer Software, 48(4), 243-255
Citations: 9
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Title: Survival Analysis Algorithms based on Decision Trees with Weighted Log-rank Criteria
Year: 2022
Authors: I. Vasilev, M. Petrovskiy, I.V. Mashechkin
Journal: ICPRAM, 132-140
Citations: 8
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Title: Sensitivity of Survival Analysis Metrics
Year: 2023
Authors: I. Vasilev, M. Petrovskiy, I. Mashechkin
Journal: Mathematics, 11(20), 4246
Citations: 5
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Title: Adaptive Sampling for Weighted Log-Rank Survival Trees Boosting
Year: 2023
Authors: I. Vasilev, M. Petrovskiy, I. Mashechkin
Journal: International Conference on Pattern Recognition Applications and Methods, 98-115
Citations: 2
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Title: Applying regularization to calculate split criterion for survival models
Year: 2024
Authors: I.A. Vasilev, M.I. Petrovskii, I.V. Mashechkin
Journal: Numerical Methods and Programming, 25(3), 357-377
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Title: Application of regularization in computing split criteria for survival analysis models
Year: 2024
Authors: I.A. Vasilev, M.I. Petrovskiy, I.V. Mashechkin
Journal: Computational Methods and Programming, 25, 357-377
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Title: Research and development of generative adversarial neural networks for reliability analysis tasks
Year: 2024
Authors: I.O. Filimonova, Y.A. Vasilev, M.I. Petrovskiy
Conference: Lomonosov Readings – 2024, Section of Computational Mathematics and Cybernetics
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Title: Critical review of survival analysis methods based on boosting ensembles
Year: 2023
Authors: Y.A. Vasilev
Conference: XXX International Scientific Conference of Students, Postgraduates, and Young Scientists
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Title: Research and development of probabilistic boosting ensemble for survival analysis
Year: 2023
Authors: I.V. Mashechkin, M.I. Petrovskiy, Y.A. Vasilev
Conference: Lomonosov Readings – 2023, Section of Computational Mathematics and Cybernetics