Networked Learning as a research direction
Learning is shaped by interaction patterns and evolving relationships. This initiative connects network science, AI and learning research to understand and responsibly support how learning networks form and function.
Kinga Sipos, PhD
Mathematician with theoretical foundations specializing in optimal mass transportation and analytical methods developed during my PhD. Her current work combines mathematical modeling with applications in data science and machine learning, including the development and teaching of courses in Mathematics for Data Science and Machine Learning.
In Learning Analytics, she collaborates with psychologists focusing on translating research into educational practice while developing practice-based approaches that inform research. Her work integrates quantitative modeling and data-driven methods to better understand and enhance learning processes.
She has extensive teaching experience at several universities in Switzerland. She develops digital learning environments that support the transition to university mathematics, with a current focus on interactive visualizations and the integration of LLMs into networked and data-informed learning settings.
Johann Stan, PhD
Dr. Johann Stan earned his PhD from Université Jean Monnet, conducting research in collaboration with the Laboratoire Hubert Curien and Alcatel-Lucent Bell Labs. His work focuses on semantic technologies and the dynamic analysis of information networks, with particular emphasis on modeling social interactions and online environments.
His research integrates semantic web technologies, linked data, and network analysis to better understand evolving digital ecosystems and improve information retrieval and recommendation systems. He has contributed to the organization of international workshops on social network analysis and semantic systems, fostering interdisciplinary exchange between network science and information systems research.
Today, Dr. Stan serves as a patent expert and member of the Swiss Learning Association, where he applies his expertise in semantic systems, machine learning, and information retrieval to the rigorous evaluation of technological innovation.