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Департамент программной инженерии был создан в 2014 году на базе отделения программной инженерии. В департаменте ведутся исследования по различным современным научным направлениям, в число которых входят: анализ и моделирование бизнес процессов, математическое моделирование, машинное обучение и искусственный интеллект, нечеткая логика, процессно-ориентированные информационные системы.
В печати
Труды конференции "Параллельные вычислительные технологии (ПаВТ'2025)". 2025.
Maksimenkova O. V., Lebedev S., Pozdnyakov D.
In bk.: Futureproofing Engineering Education for Global Responsibility: Proceedings of the 27th International Conference on Interactive Collaborative Learning (ICL2024), Volume 4. Springer, 2025. P. 116-125.
В печати
Ryabtsev D., Vasilyev Boris, Shershakov S.
Computer Science ::Computer Vision and Pattern Recognition. 2501.14689. arXiv, 2025
Коллоквиум факультета компьютерных наук. "Process Mining: Data Science in Action"
Eindhoven University of Technology
Process Mining: Data Science in Action
Время: 16:40 - 18:00
Место: Кочновский проезд, дом 3, лекционный зал Декарт (3 этаж)
Аннотация
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using a booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, prof. Wil van der Aalst refers to it in his talk as "data science in action". Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development.
Wil van der Aalst - Process Mining Data Science in Action (PDF, 1.03 Мб)