Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.
Barinova M., Osenkov E., Pochinka O., Regular and Chaotic Dynamics 2025 Vol. 30 No. 2 P. 226–253
In investigating dynamical systems with chaotic attractors, many aspects of global behavior of a flow or a diffeomorphism with such an attractor are studied by replacing a nontrivial attractor by a trivial one [1, 2, 11, 14]. Such a method allows one to reduce the original system to a regular system, for instance, of a Morse – Smale ...
Pochinka O., Босова А. А., Журнал Средневолжского математического общества 2019 Т. 21 № 2 С. 164–174
Периодические данные диффеоморфизмов с регулярной динамикой на поверхностях изучались с помощью дзета-функции в серии уже классических работ таких авторов, как П. Бланшар, Дж. Фрэнкс, С. Нарасимхан, С. Баттерсон, Дж. Смилл и др. Описание периодических данных градиентно-подобных диффеоморфизмов поверхностей было дано в работе А. Безденежных и В. Гринеса посредством классификации периодических преобразований поверхности, полученных Дж. Нильсеном. ...