The directions, scientific interests, and technologies of the AI Center — from machine learning and computer vision to robotics and industrial digitalization. Work at various stages: from ideas and directions to applied research and prototypes.
A computer-aided design system for pipework layouts in which generative AI proposes layout options and finite-element analysis, embedded inside the generation loop, decides which of them are admissible.
An edge-AI platform that combines solar generation, biogas, storage, and EV charging into a single controllable flexibility resource for distribution grids with a high share of renewables.
A multi-agent AI system built on Claude for automated preparation of grant applications to European programmes — from parsing the call to a ready submission package.
A lecture course on the modern AI-assisted software-development workflow with the Claude assistant — from problem statement to finished code.
Developing machine-learning methods within a UNESCO and CBPF (Brazil) programme that gives researchers remote access to AI infrastructure, mentorship, and participation in joint scientific tasks. The lab is preparing three individual research applications.
Image classification, detection, and segmentation — an overview of typical architectures and use cases.
Attention, context, and language models — how they work and where they are applied in modern NLP.
Running neural networks outside the cloud — trade-offs between accuracy, speed, and compute resources.
Sensors, navigation, and decision-making in autonomous and smart systems.
A typical set of technologies and practices for machine-learning research — from data to model.
Propose research or an applied problem — we'll consider collaboration with students and the Center's laboratory.