Научные руководители
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Леоненко Василий Николаевичкандидат физико-математических наук vnleonenko@itmo.ru Структурное подразделение: исследовательский центр в сфере искусственного интеллекта "Сильный искусственный интеллект в промышленности" Должность: старший научный сотрудник Структурное подразделение: факультет цифровых трансформаций Должность: доцент (квалификационная категория "ординарный доцент") Профиль: 1.2.1 - Искусственный интеллект и машинное обучение 1.2.1. - Искусственный интеллект и машинное обучение 1.2.2. - Математическое моделирование, численные методы и комплексы программ 2.3.1. - Системный анализ, управление и обработка информации, статистика 2.3.4. - Управление в организационных системах 05.13.18 - Математическое моделирование, численные методы и комплексы программ Область интересов: Математическая эпидемиология. Применение математического моделирования и искусственного интеллекта для решения задач эпидемиологии и здравоохранения. Применение математического моделирования и искусственного интеллекта для решения задач эпидемиологии и здравоохранения. Рабочий язык: Английский, Испанский, Русский, Французский |
Публикации руководителя
| Выходные данные | Год | Индексирование в БД |
| 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 | 2023 | Scopus, Web of Science |
| 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 | 2023 | Scopus, Web of Science |
| 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 | 2023 | Scopus, ВАК, РИНЦ |
| 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 | 2022 | Scopus, Web of Science |
| 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 | 2022 | Scopus, Web of Science |
| 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 | 2022 | Scopus, Web of Science |
| 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 | 2022 | Scopus, Web of Science |
| 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 | 2021 | Scopus, Web of Science |
| 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 | 2021 | Scopus, Web of Science |
| 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 | 2021 | Scopus, Web of Science |
| 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 | 2021 | Scopus, Web of Science, ВАК |
| 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 | 2021 | Scopus, Web of Science |
| 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 | 2020 | Scopus, Web of Science |
| 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 | 2020 | |
| 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 | 2020 | Web of Science |
| 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 | 2020 | Scopus, Web of Science |
| 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 | 2020 | Web of Science |
| 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 | 2020 | RSCI, Scopus, ВАК, РИНЦ |
| 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 | 2019 | Scopus, Web of Science |
| 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 | 2019 | Scopus, Web of Science |
| 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 | 2019 | RSCI, Scopus, ВАК, РИНЦ |
| Leonenko V.N., Bobashev G. Analyzing influenza outbreaks in Russia using an age-structured dynamic transmission model//Epidemics, 2019, Vol. 29, pp. 100358 | 2019 | Scopus, Web of Science |
| 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 | 2019 | Scopus, Web of Science |
| 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 | 2018 | Scopus, Web of Science |
| 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 | 2018 | |
| 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 | 2018 | Scopus |
| 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 | 2017 | Scopus, Web of Science |
| 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 | 2017 | Scopus, Web of Science |
| 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 | 2017 | Scopus, Web of Science |
| 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 | 2017 | Scopus, Web of Science |
| 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 | 2016 | ВАК, РИНЦ |
| 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 | 2016 | Scopus, Web of Science, ВАК |
| Слоот П., Холыст Я., Кампис Ж., Лис М., Митягин С.А., Иванов С.В., Боченина К.О., Гулева 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 | 2016 | ВАК, РИНЦ |
| 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 | 2016 | Scopus, Web of Science |
| 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 | 2016 | Scopus, Web of Science |
| 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 | 2015 | Scopus, Web of Science |