Smirnov E., Dunaenko S., Kudinov S., Antonov A. Using Machine Learning Methods in City Park Design Automation. CUPUM2021 digital book of abstracts. 2021. pp. 1-7.
Smirnov E., Kudinov S. Using a Genetic Algorithm for Planning Interesting Tourist Routes in the City on the Basis of Open Street Map Data. IEEE Congress on Evolutionary Computation, CEC 2021. 2021. pp. 264-271.
Antonov A., Khodnenko I., Kudinov S. Facade deterioration prediction with the use of machine learning methods, based on objective parameters and e-participation data. Procedia Computer Science. 2021. Vol. 193. pp. 42-51.
Landsman D., Kats P., Nenko A., Kudinov S., Sobolevsky S. Social Activity Networks Shaping St. Petersburg. Proceedings of the 54th Hawaii International Conference on System Sciences, HICSS 2021. 2021. pp. 1149-1158.
Kudinov S., Antonov A., Ilina E. Specifying Spatial and Temporal Characteristics of Increased Activity of Users of E-Participation Services. Communications in Computer and Information Science. 2020. Vol. 1349. pp. 156–171.
Smirnov E., Dunaenko S., Kudinov S. Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks. Geo-spatial Information Science. 2020. Vol. 23. No. 4. pp. 362-374.
Kudinov S., Ilina E., Antonov A. Analyzing Civic Activity in the Field of Urban Improvement and Housing Maintenance Based on E-Participation Data: St. Petersburg Experience. Communications in Computer and Information Science. 2020. Vol. 1135. pp. 88-102.
Спирова Н.Ю., Кудинов С.А. Разработка классификатора сущностей городской среды на основе правоотношений для задач управления умным городом. Региональная информатика (РИ-2020): труды XVII конференции (Санкт-Петербург, 28-30октября 2020г.). 2020. Т. Часть 1. С. 40-41.
Golubev K., Fedorov V., Zagarskikh A.S., Karsakov A., Kudinov S. Towards an automated pipeline for visualization of complex spatiotemporal urban data. CEUR Workshop Proceedings. 2020. Vol. 2721. pp. нет такой статьи.
Kudinov S., Smirnov E., Dunaenko S. Using Multi-Agent Simulation to Predict Natural Crossing Points for Pedestrians and Choose Locations for Mid-Block Crossings. Proceedings of CUPUM2019. 2019. pp. 78-93.
Kudinov S., Ильина E., Grekhneva E. Exploring the connection between the existence of local web communities and civic activity: St. Petersburg case study. Communications in Computer and Information Science. 2019. Vol. 947. pp. 334-347.
Пешеходные дорожные сети: типичные ошибки проектирования и методы их решения
Автоматическая оценка жизнеспособности дорожно-тропиночных сетей по критерию величины контрольного угла
МЕТОД ПОИСКА КРАТЧАЙШЕГО ПУТИ С ПОМОЩЬЮ ПОСТРОЕНИЯ КАРТЫ ИЗОХРОН НА ОСНОВЕ ОПТИМАЛЬНЫХ СЕТЕЙ ПЕШЕХОДНЫХ ДОРОЖЕК
Nikolaev A.G., Kudinov S.A. Development of recommendations on the planning structure and street design in the cities with cold climate. Proceedings of 54th ISOCARP Congress (Bodo, Norway, October 1-5, 2018). Cool planning: changing climate & our urban future. 2018. pp. 515-523.
Kudinov S.A., Smirnov E.V., Malyshev G.N., Khodnenko I. Planning Optimal Path Networks Using Dynamic Behavioral Modeling. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018. Vol. 10861. pp. 129-141.
Khodnenko I., Kudinov S., Smirnov E. Walking distance estimation using multi-agent simulation of pedestrian flows. Procedia Computer Science. 2018. Vol. 136. pp. 489-498.