Darwish A., Leonenko V.N. Reducing computational costs of agent-based modeling of respiratory infection spread using a machine learning-based surrogate model. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2025. Vol. 25. pp. в печати?.
Korzin A., Leonenko V. Lightweight Models for Influenza and COVID-19 Prediction in Heterogeneous Populations: A Trade-Off Between Performance and Level of Detail. Mathematics. 2025. Vol. 13. No. 9. pp. 1385.
Korzin A.I., Kaparulin T.I., Leonenko V.N. Assessing the Effect of Influenza Vaccination Strategies Using Multi-agent Modeling. 3rd International Conference on Problems of Informatics, Electronics and Radio Engineering, PIERE 2024. 2024. pp. 1000-1003.
Тычкова В.И., Леоненко В.Н., Даниленко Д.М. Предсказательное моделирование эволюции респираторных вирусов: современные возможности и ограничения [Predictive Modeling of Respiratory Virus Evolution: Current Capabilities and Limitations]. Математическая биология и биоинформатика [Mathematical Biology and Bioinformatics]. 2024. Т. 19. № 2. С. 579-592.
Senichev S.D., Fandeev A.A., Leonenko V.N. Accelerating multiagent epidemic modeling with surrogate-based methods. 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). 2024. pp. 220-223.
Leonenko V.N. When a Pandemic Comes to Town: Combating Propagation of Novel Viruses in Russian Cities Using Statistical and Mathematical Modeling. 3rd International Conference on Problems of Informatics, Electronics and Radio Engineering, PIERE 2024. 2024. pp. 990-995.
Урбанистические факторы динамики эпидемических ОРВИ: анализ на основе мультиагентых моделей
Использование интерпретируемых алгоритмов машинного обучения для моделирования динамики заболеваемости во время эпидемии
Abramova Y., Leonenko V. The Past Helps the Future: Coupling Differential Equations with Machine Learning Methods to Model Epidemic Outbreaks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2024. Vol. 14835. pp. 247–254.
Korzin A.I., Leonenko V.N. Uncertainty Quantification for the Stochastic Modeling of Influenza Propagation: How Many Simulation Runs is Enough. 2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM). 2024. pp. 2200-2203.
Korzin A.I., Kaparulin T.I., Leonenko V.N. Assessing the Applicability of the Multiagent Modeling Approach to the Epidemic Surveillance of COVID-19 in Russian Cities. 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). 2024. pp. 237-242.
прогнозирование распространения заболеваний на основе пространственно-временных данных с использованием сверточных нейронных сетей
Леоненко В.Н., Корзин А.И., Даниленко Д.М. Применение математических моделей динамики заболеваемости эпидемическими ОРВИ для увеличения эффективности эпидемиологического надзора [Application of Mathematical Models of the Dynamics of the Epidemic Acute Respiratory Viral Infections to Increase the Efficiency of Epidemiological Surveillance]. Математическая биология и биоинформатика [Mathematical Biology and Bioinformatics]. 2023. Т. 18. № 2. С. 517–542.
Sahatova K., Kharlunin A., Leonenko V. A Novel Approach to Modeling and Visualisation of Epidemic Outbreaks: Combining Manual and Automatic Calibration. Proceedings - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023. 2023. pp. 221-226.
Sahatova K., Kharlunin A., Huaman I., Leonenko V. Accounting for Data Uncertainty in Modeling Acute Respiratory Infections: Influenza in Saint Petersburg as a Case Study. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2023. Vol. 10475. pp. 286-299.
Huaman I., Leonenko V. Does Complex Mean Accurate: Comparing COVID-19 Propagation Models with Different Structural Complexity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2023. Vol. 10475. pp. 270–277.
Kharlunin A., Huaman I., Leonenko V. Inferring Values of Epidemic Indicators via SEIR Models to Enhance Epidemiological Surveillance in Russia. Proceedings - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023. 2023. pp. 202-207.
Matveeva A., Leonenko V. Application of Gaussian process regression as a surrogate modeling method to assess the dynamics of COVID-19 propagation. Procedia Computer Science. 2022. Vol. 212. pp. 340-347.
Huaman I., Plesovskaya E.P., Leonenko V.N. Matching model complexity with data detail: influenza propagation modeling as a case study. 2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). 2022. pp. 650-654.
Leonenko V. A Hybrid Modeling Framework for City-Scale Dynamics of Multi-strain Influenza Epidemics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2022. Vol. 13352. pp. 164-177.
Leonenko V.N., Kaliberda Y., Muravyova Y.V., Artyukh V. A Decision Support Framework for Periprosthetic Joint Infection Treatment: A Cost-Effectiveness Analysis Using Two Modeling Approaches. Journal of Personalized Medicine. 2022. Vol. 12. No. 8. pp. 1216.
Pasala K., Putnikov S., Leonenko V.N. Calibrating deterministic compartmental models of infection dynamics using neural network and data sampling approaches. Proceedings - 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2022. 2022. pp. 100-103.
Danilenko D.M., Eropkin M.Y., Leonenko V.N., Konovalova N., Petrova P., Zheltukhina A., Vassilieva A. Assessment of rat polyclonal antisera's suitability in hemagglutination inhibition assay for influenza surveillance and antigenic mapping. Journal of Virological Methods. 2021. Vol. 293. pp. 114170.
Вероятностные методы анализа данных: учебно-методическое пособие по выполнению лабораторных работ
Leonenko V.N. Modeling Co-circulation of Influenza Strains in Heterogeneous Urban Populations: The Role of Herd Immunity and Uncertainty Factors. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. Vol. 12744. pp. 663-669.
Leonenko V.N., Kaliberda Y., Artyuk V. A modeling framework for decision support in periprosthetic joint infection treatment. Studies in health technology and informatics. 2021. Vol. 285. pp. 106-111.
Kaliberda Y., Leonenko V.N., Artyukh V. Towards cost-effective treatment of periprosthetic joint infection: from statistical analysis to Markov models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. Vol. 12744. pp. 494-505.
Leonenko V.N. Herd immunity levels and multi-strain influenza epidemics in Russia: a modelling study. Russian Journal of Numerical Analysis and Mathematical Modelling. 2021. Vol. 36. No. 5. pp. 279-291.
Leonenko V.N., Danilenko D.M. Modeling the dynamics of population immunity to influenza in Russian cities. ITM Web of Conferences. 2020. Vol. 31. pp. 03001.
Leonenko V.N., Arzamastsev S., Bobashev G. Contact patterns and influenza outbreaks in Russian cities: A proof-of-concept study via agent-based modeling. Journal of Computational Science. 2020. Vol. 44. pp. 101156.
Leonenko V.N., Kovalchuk S.V. Analyzing the spatial distribution of individuals predisposed to arterial hypertension in Saint Petersburg using synthetic populations. ITM Web of Conferences. 2020. Vol. 31. pp. 03002.
Попова Е.П., Леоненко В.Н. Прогнозирование реакции пользователей в социальных сетях методами машинного обучения [Machine learning methods for forecasting of social network users’ reactio]. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2020. Т. 20. № 1(125). С. 118-124.
Arzamastsev S.A., Leonenko V.N. A demographic microsimulation model for the long-term evolution of synthetic populations in Saint-Petersburg. Доклады Международной конференции "Математическая биология и биоинформатика". 2020. Vol. 8. pp. 157-161.
Leonenko V.N. Analyzing the Spatial Distribution of Acute Coronary Syndrome Cases Using Synthesized Data on Arterial Hypertension Prevalence. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12140 LNCS. pp. 483-494.
Bates S., Leonenko V.N., Rineer J., Bobashev G. Using synthetic populations to understand geospatial patterns in opioid related overdose and predicted opioid misuse. Computational and Mathematical Organization Theory. 2019. Vol. 25. No. 1. pp. 36-47.
Owusu P.A., Leonenko V.N., Mamchik N.A., Skorb E.V. Modeling the growth of dendritic electroless silver colonies using hexagonal cellular automata. Procedia Computer Science. 2019. Vol. 156. pp. 43-48.
Leonenko V.N., Lobachev A.I., Bobashev G. Spatial modeling of influenza outbreaks in Saint Petersburg using synthetic population. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. Vol. 11536. pp. 492-505.
Карпова Л.С., Соминина А.А., Даниленко Д.М., Волик К.М., Леоненко В.Н. Оценка эффективности базовых линий и порогов интенсивности эпидемий по результатам традиционного надзора за гриппом [Evaluation of the effectiveness of baselines and thresholds intensity epidemics, according to the results of traditional surveillance for influenza]. Эпидемиология и вакцинопрофилактика [Epidemiologiya i Vaktsinoprofilaktika]. 2019. Т. 18. № 4. С. 4-13.
Leonenko V.N., Bobashev G. Analyzing influenza outbreaks in Russia using an age-structured dynamic transmission model. Epidemics. 2019. Vol. 29. pp. 100358.
Bates S., Leonenko V.N., Rineer J., Bobashev G. Using synthetic populations to understand geospatial patterns in opioid related overdose and predicted opioid misuse. International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, BRiMS 2018. 2018.
Leonenko V.N., Novoselova Y.K. Influence of External Factors on Inter-City Influenza Spread in Russia: A Modeling Approach. Trends in Biomathematics: Modeling, Optimization and Computational Problems. 2018. pp. 375-389.
Leonenko V.N., Ivanov S.V. Prediction of influenza peaks in Russian cities: comparing the accuracy of two SEIR models. Mathematical Biosciences and Engineering. 2018. Vol. 15. No. 1. pp. 209–232.
Математическая эпидемиология: учебно-методическое пособие по выполнению лабораторных работ
Leonenko V.N., Bochenina K.O., Kesarev S.A. Influenza peaks forecasting in Russia: assessing the applicability of statistical methods. Procedia Computer Science. 2017. Vol. 108. pp. 2363-2367.
Анализ и моделирование темпоральных комплексных сетей
Seleznev N.E., Leonenko V.N. Absolute humidity anomalies and the influenza onsets in Russia: A computational study. Procedia Computer Science. 2017. Vol. 119. pp. 224-233.
Artzrouni M., Leonenko V.N., Mara T.A. A syringe-sharing model for the spread of HIV: application to Omsk, Western Siberia. Mathematical Medicine and Biology. 2017. Vol. 34. No. 1. pp. 15-37.
Seleznev N.E., Leonenko V.N. Boosting Performance of Influenza Outbreak Prediction Framework. Communications in Computer and Information Science. 2017. Vol. 745. pp. 374-384.
Анализ и моделирование темпоральных комплексных сетей
Леоненко В.Н., Новоселова Ю.К., Онг К. Предсказание пиков эпидемий гриппа в Санкт-Петербурге с помощью популяционных математических моделей. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2016. Т. 16. № 6(106). С. 1145–1148.
Слоот П., Холыст Я., Кампис Ж., Лис М., Митягин С.А., Иванов С.В., Боченина К.О., Павлова В.Ю., Мухина К.Д., Насонов Д.А., Бутаков Н.А., Леоненко В.Н., Ланцева А.А., Бухановский А.В. Суперкомпьютерное моделирование критических явлений в сложных социальных системах. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2016. Т. 16. № 6(106). С. 967-995.
Leonenko V.N., Ivanov S.V. Fitting the SEIR model of seasonal influenza outbreak to the incidence data for Russian cities. Russian Journal of Numerical Analysis and Mathematical Modelling. 2016. Vol. 31. No. 5. pp. 267-279.
Leonenko V.N., Novoselova Y.K., Ong K.M. Influenza Outbreaks Forecasting in Russian Cities: Is Baroyan-rvachev Approach Still Applicable?. Procedia Computer Science. 2016. Vol. 101. pp. 282-291.
Leonenko V.N., Ivanov S.V., Novoselova Y.K. A computational approach to investigate patterns of acute respiratory illness dynamics in the regions with distinct seasonal climate transitions. Procedia Computer Science. 2016. Vol. 80. pp. 2402-2413.
Leonenko V.N., Pertsev N.V., Artzrouni M. Using high performance algorithms for the hybrid simulation of disease dynamics on CPU and GPU. Procedia Computer Science. 2015. Vol. 51. pp. 150-159.
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