KMi is a diverse and multidisciplinary R&D lab that has been at the forefront of innovation since 1995, conducting research in computing technologies for social and environmental good. Our research spans Semantic Technologies, Artificial Intelligence, Educational Media, Social Data Science, Scholarly Data, Blockchain, Citizen Science, Collective Intelligence, Smart Cities, and others.
Upcoming Seminar
3D shape understanding of plants and trees: recovering semantics with digital geometry
This event will take place on Tuesday 22 April 2025
Prof. Franck Hétroy-Wheeler - University of Strasbourg
3D digital shapes are now ubiquitous, from industrial digital twins and mock-ups to virtual environments and characters. Unfortunately, they are mostly represented as a set of basic geometric...
Showcase
People
My research specialisation is in Computational Linguistics and Data Science, with a focus on communicating complex data and making information and data (particularly telemetric data) accessible...
Testimonials
"If you are or want to be a brilliant mind, this is where you want to be!"
Valentina Presutti, Institute of Cognitive Science and Technologies, Italy
"I cannot imagine going to a conference without experiencing deep scientific conversations with KMiers!"
Raphaël Troncy, EURECOM: Graduate School & Research Center, France
"Top location for SW research for decades and going strong!"
Pascal Hitzler, Kansas State University, USA
Publications
Mikroyannidis, A., Ekuban, A., Kwarteng, J. and Domingue, J. (2025) Best Practices for the Responsible Adoption of Generative AI in Higher Education, Proceedings, 114, 1, pp. 1-8
Herodotou, C., Carr, J., Shrestha, S., Comfort, C., Bayer, V., Maguire, C., Lee, J., Mulholland, P. and Fernandez, M. (2025) Prescriptive analytics motivating distance learning student action: A case study of a student-facing dashboard, LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), Dublin, Ireland
Borrego, A., Dessì, D., Ayala, D., Hernández, I., Osborne, F., Recupero, D., Buscaldi, D., Ruiz, D. and Motta, E. (2025) Research hypothesis generation over scientific knowledge graphs, Knowledge-Based Systems, pp. (Early access), Elsevier
