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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
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.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
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.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
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.

 

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Multimodal EEG, ECG, and video dataset of yoga practitioners during concentration and mind-wandering tasks

Scientific data. 2026. Vol. 13. Article 850.
Kashevnik A., Glekler E., Artemenko E., Shoshina I., Brak I.

We present a multimodal dataset containing electroencephalography (EEG), electrocardiography (ECG), and video recordings from 49 participants. Each participant completed a single session lasting approximately 45 minutes. During each session they performed five tasks: resting state, inward concentration (focusing on the center of the forehead), outward concentration (visual search), and mind-wandering. EEG data were recorded from 64 channels at 2048 Hz; ECG and frontal video were collected simultaneously. The dataset includes 49 validated recordings: 25 from experienced yoga practitioners and 24 from individuals without prior experience in yoga or other self-regulation practices. The recordings are synchronized and structured for convenient use in cross-modal analyses. This dataset may support research in attention, concentration, meditation, affective computing, and multimodal signal integration. All data are anonymized and organized for easy access and reuse.

Research target: Biology Health Studies Psychology
Language: English
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Keywords: EEGmultimodalConsciousnessNeurophysiology
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