Jessie Kennedy

Professor Jessie Kennedy is an Enhanced Associate at Edinburgh Napier University's School of Computing Engineering and the Built Environment, specializing in information visualization and human-computer interaction. She is a prominent member of the Centre for Algorithms, Visualisation and Evolving Systems, with extensive contributions to visualization theory and practice across multiple domains.

Her research interests focus on Information Visualization, Network Visualization, Biological Visualization, and Argument Visualization. Professor Kennedy has developed innovative visualization techniques for complex data structures including multiple overlapping classification hierarchies, dynamic networks, and Bayesian networks. Her work bridges theoretical foundations with practical applications in cybersecurity, biology, and education.

Professor Kennedy's publications reveal consistent contributions to visualization theory and applications over two decades. Her recent work includes visualization for insider threat detection, argument exploration techniques, and embodied dance learning systems through the CAROUSEL+ project. Her research demonstrates an evolution from foundational visualization techniques to complex applications in diverse domains including biological data, cybersecurity, and virtual reality environments.

Professor Kennedy has been instrumental in securing significant research funding from organizations including the European Commission and Innovate UK, with projects totaling over £1.3 million. Her Scottish Woodlands KTP project focused on unified access to forest management data, while the CAROUSEL+ project (funded by Horizon 2020) explores how AR and AI technologies can enhance social interaction in virtual and hybrid events.

She leads the Centre for Algorithms, Visualisation and Evolving Systems research group which has produced over 78 outputs. Her laboratory work focuses on developing practical visualization tools that address real-world challenges in data exploration and understanding, with particular emphasis on biological data visualization, network analysis, and educational applications.