๐ Teaching Recognition
Runner-up Supervisor of the Year 2020, as voted for by the Edinburgh University Students' Association. Long-listed for Teacher of the Year 2024. Nominated Supervisor of the Year 2025. Multiple nominations for Teacher of the Year, Supervisor of the Year, and Personal Tutor of the Year from 2021-2024, including Informatics Staff Awards 2021.
๐ฌ Research Focus
My research explores the intersection of artificial intelligence, machine learning, creative arts, and embodiment with a particular focus on making AI more accessible and impactful in educational and creative contexts.
Academic Background
I am a Lecturer at the School of Informatics, University of Edinburgh, where I teach and conduct research in artificial intelligence and machine learning. My work spans both theoretical foundations and practical applications, with a strong emphasis on collaborative research and innovative teaching methods.
My passion lies in bridging the gap between cutting-edge AI research and real-world applications, particularly in education and creative domains. I believe in making complex AI concepts accessible to students and practitioners from diverse backgrounds.
As a researcher, I primarily focus on Applied Machine Learning, studying models of human behaviour, specifically related to their preferences and how those are expressed in their interactions with systems and other users, typically in online recommender systems.
More recently, I have been working with my PhD student Patrick Kage on better incorporating downstream tasks for Weakly Semi-Supervised Learning. Past projects involved learning simple and efficient models of human preferences, as well as using recommender systems for the efficient coordination of a large number of non-communicating agents.
I am educated in Operations Research and Production and Management Engineering, and am available for consulting services.
Research Areas
๐ง Artificial Intelligence
Machine learning, deep learning, and AI systems development
๐ค Embodied AI
AI systems with physical form that perceive, reason, and act in real-world environments (especially robotics)
๐ Education Technology
AI in education, innovative teaching methods, and learning analytics
๐จ Creative AI
Generative AI, AI art, and creative applications of machine learning
Teaching Philosophy
I believe in creating an accessible and engaging learning environment where students can explore AI concepts through hands-on experience and real-world applications. My teaching approach combines theoretical understanding with practical implementation, encouraging students to think critically about the application of AI and master the ability to think about it at the system level โ a powerful tool in their creative and problem solving toolkit.
I'm particularly interested in developing innovative teaching methods that leverage AI technology itself to enhance the learning experience, making complex concepts more accessible and engaging for all students.
At the heart of my approach is a commitment to kindness and empowerment. I support my students by making resources accessible and understandable, providing just enough scaffolding for them to dive into subjects with enthusiasm. However, I believe that students are ultimately responsible for their own learning journey and success. My role is to create the conditions for growth while cultivating their sense of responsibility and ownership over their educational path.