Applied AI and software engineering​​

Supporting scientists is the primary objective, and computational methods serve as both a testbed and an example of large-scale scientific activity to better understand scientific needs and to adapt knowledge models and research platform features accordingly.
Applied AI & software engineering

Overview

Our methodology lowers technical barriers for scientists and educators through adaptive learning and advanced analytics, with AI-driven avatars and agentic interfaces central to education, personalized medicine, and the real-world application of scientific discoveries. We focus on applied tasks involving digital twins of different directions like personal or medical ones, and systems, integrating data processing methods into knowledge twin operations.

Our Projects

Explore our innovative research work

Discover a selection of our key projects that highlight our commitment to advancing education through research.

Fan Blade Defect Monitoring Service for Aircraft Engines

Remotely Controlled Unmanned Underwater Vehicle

From Task to Code: Automating ML Pipeline Generation with Linguacodus

AI-agents for Life Science Industry

Publications

  • Ferrario, G., Mikriukov, A., Plaksin, Y., Sitnikov, V., Succi, G., Tormasov, A., & Trofimova, E. (2025, May). Evaluating cost-effectiveness and coherence of LLMs for supplement recommendations using routing techniques. In 2025 10th International Conference on Machine Learning Technologies (ICMLT) (pp. 350-354). IEEE.

Research Team

Meet Our PIs

Discover our teams diverse expertise and how their qualifications drive innovative solutions in education and research.

Prof. Dr. Alexander Tormasov

Prof. Dr. Andrey Ustyuzhanin

Prof. Dr. Petr Popov

Prof. Dr. Giancarlo Succi

Partner with us to innovate together