Personal Statement
Terry has been research in the area of agent-based computing and knowledge-based systems and services for the last 30 years, and has published more than 195 peer-reviewed papers in the area. His specific interest is in the use of ontological knowledge for the support of agent-based service discovery and provision and is currently exploring the exploration of dialogue-based negotiation approaches to establish contextually-relevant ontological alignment between interacting agents on the fly. This supports the longer term aim of describing, discovering and utilising capability descriptions that agents offer or exploit when collaborating within open and pervasive environments, such as the Internet of Things. He has received numerous research awards, including a Best Industrial Paper award in 2006, and two Distinguished Research paper awards in 2011 & 2012 that recognised his fundamental contribution to his research field his research. He was Program co-chair for the International Semantic Web Conference in 2023, and is a member of SWSA - the Semantic Web Science Association, responsible for promoting and exchanging scholarly work in Semantic Web and related fields throughout the world. He is a Senior Fellow of the Higher Education Authority (SFHEA), and was also awarded a University Learning & Teaching Excellence award in 2013, 2016, 2019 and 2022 for innovative and technology enhanced teaching. His teaching was also recognised by the student body in 2016 when he was awarded the Guild of Students Best Teacher (Faculty of Science) Award.

Research Overview
My research interests lie within the use of Knowledge by distributed autonomous systems, or Agents. These agents may provide specific support for an individual (for example, Agentic AI), or within an autonomous community of agents (Multi-Agent Systems). Much of my focus has been on how formal, symbolic knowledge is defined and shared between agents, thus allowing collaboration and co-operation, using a variety of AI based techniques, through heuristic search, dialogue and negotiation, machine learning (neurosymbolic) and more recently, through the exploitation of GAI (generative AI) techniques.