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.
At the Knowledge Media Institute (KMi), we transform bold ideas into innovative technologies with real-world impact on society and the environment. We understand technology, and people, and how to harness the latest technical advancements to tackle today's and tomorrow's challenges. For over 30 years, KMi has led AI-driven breakthroughs in knowledge and science, reinforcing research, education, and discovery with intelligent, ethical, and inclusive solutions. Our work empowers all learners, with a strong focus on those from less advantaged backgrounds, ensuring education remains accessible and equitable. We specialise in Benevolent Tech, developing powerful tools for combating online harms, reshaping life in smart cities, reconnecting people with nature to save the planet, and advancing the world's understanding of critical AI developments.
Our expertise in AI ethics, explainability, and human-AI collaboration is more crucial than ever, offering key insights for the responsible adoption of AI in education, research, and society. Our latest advancements include leveraging generative AI for personalised lifelong learning, powering a global open research system serving 30 million monthly users, and developing AI-driven tools to track and predict the progress and retention of over 100,000 students. What sets KMi apart is our pioneering hybrid approach; blending human and symbolic understanding with machine intelligence and analysis. This fusion enables us to move beyond conventional tech solutions, driving meaningful change through groundbreaking human-centred innovations.
KMi prides itself on being diverse, equitable, non-hierarchical and people-oriented, facilitating the free generation of ideas and their robust deliberation. It provides an agile and supportive environment that removes barriers to creativity, fosters innovation and enables talent to thrive.
Upcoming Seminar
Enhancing Fairness in Machine Learning: Identifying and Mitigating Bias with a Focus on Gender Bias in Finance
This event will take place on Tuesday 29 July 2025
Dr. Ángel Pavón Pérez - KMi, The Open University
Machine Learning systems increasingly shape critical decisions—who gets a loan, who receives healthcare support, who’s flagged for risk. However, the data behind these systems often...
Showcase
People
Suchetha is a research associate at KMi, part of the Big Scientific Data and Text Analytics Group (BSDTAG) team: http://bsdtag.kmi.open.ac.uk/. She finished her PhD on "Language Models for Citation...
I am a Data Engineer at the OUAnalyse team and currently also a technical lead of the project. As a part-time PhD student, I am investigating how Learning Analytics can be used to target awarding...
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
Tsaneva, S., Dessì, D., Osborne, F. and Sabou, M. (2025) Knowledge graph validation by integrating LLMs and human-in-the-loop, Information Processing & Management, 62, Elsevier
Coughlan, T., Rienties, B., Domingue, J., Herodotou, C., Ullmann, T., Bektik, D., Edwards, C., Whitelock, D., Coughlan, E. and Tessarolo, F. (2025) Holding a lead, or the tail wagging the dog? Exploring educator influence over the behaviour of AI Digital Assistants, EDEN 2025 Annual Conference, Bologna, Italy
Antonini, A., Cosar, S., Naja, I., Salman, H., Jamie, M., Pasquale, I. and Giacinto, B. (2025) Smartphone as a Sensor in mHealth: Narrative Overview, SWOT Analysis, and Proposal of Mobile Biomarkers, Sensors, 25
