Research areas of interest:
Machine learning and data analysis. Research on the application of deep neural networks in medical and mobile image classification, with a focus on transfer learning and model interpretability. Mathematical and stochastic modelling of dynamic processes, including analysis of economic phenomena and econometric modelling. Integration of AI methods with sensor systems in augmented reality (AR) and applications in indoor localisation. Research on knowledge extraction from the scientific literature using large language models (LLM) and supervised learning models (ML), with particular emphasis on the planning of syntheses of porous materials (zeolites). Inverse modelling, recommendation systems design and database development. Integration of NLP methods, RAG and multi-agent architectures in systems supporting chemical experiments.

Science communication and knowledge transmission. Interests include modern forms of communicating research results, critical-thinking and creative communication problem solving and working with the media. Particular emphasis is placed on building science-society dialogue through narrative, visual and interactive tools.