Alexander Brecko

Alexander Brecko is a Research Engineer at the Kempelen Institute of Intelligent Technologies (KInIT), where he works on applied artificial intelligence, machine learning, and AI-driven solutions for real-world use cases. His academic background is closely connected with business informatics, computer science, edge computing, and machine learning. During his bachelor’s and master’s studies, he focused on data processing at the network’s edge, and later continued as a PhD student at the Technical University of Košice with the research topic “Machine Learning for Edge Computing”. This shaped his professional focus on federated learning, deep learning, and AI methods suitable for devices with limited computational resources. 

His student and early research life was strongly project-oriented. During his PhD studies, he led AI-focused research projects involving image, video, and time-series data processing. As a consultant, he also consulted on five master’s theses and ten bachelor’s theses, supporting students in their academic and technical work. In parallel, he gained practical software engineering experience as a full-stack developer on a digital twin project for Slovakia. His publication record reflects a consistent focus on edge computing and applied AI, including topics such as federated learning, edge AI accelerators, cloud computing, and digital health records. 

At KInIT, his recent work connects academic research with applied AI systems that have practical and societal impact. He is involved in projects such as Dig4Health, which focuses on personalised digital health risk management and uses AI, data analysis, recommendation methods, and LLM-based conversational assistance to support people living with obesity and related health risks. Through this work, he contributes to AI solutions designed to be useful, trustworthy, and applicable in real-world healthcare and digital coaching scenarios.