Dr Pete Burnap
I am a Senior Lecturer in the School of Computer Science & Informatics and Social Computing research priority area lead in the Complex Systems research group. I have developed a reputation for data-driven, innovative, and interdisciplinary research that broadly contributes to the growing field of Data Science, working closely with the Cardiff School of Social Sciences and School of Engineering. I am an applied computer scientist with a principal focus on data and computational methods to improve understanding, operations and decision making outside of academia, while contributing to the academic fields of Social Computing, Web Science and Cybersecurity.
These three fields are integrated within my research through the analysis and understanding of Web-enabled human and software behaviour, with a particular interest in emerging and future risks posed to civil society, business (economies) and governments. I achieve this using computational methods such as machine learning and statistical data modelling, and interaction and behaviour mining, opinion mining and sentiment analysis to derive key features of interest.
Education and qualifications
- 2010: PhD (Cyber Security in Collaborative Distributed Systems), Cardiff University
- 2002: BSc Computer Science. Cardiff University
- 2016 - present: Senior Lecturer, Cardiff School of Computer Science & Informatics
- 2012 - 2016: Lecturer, Cardiff School of Computer Science & Informatics
Honours and awards
- Lloyds Science of Risk Prize Runner Up, 2015
Research interests include:
- Social Media Analysis: Developing new algorithms and implementing computational analysis tools (often informed by social theory) to better understand online social interaction and behaviour;
- Supporting Decision Making: Building systems to support intelligence gathering, risk assessment, and decision making - "extracting knowledge from data";
- Big Data and Text Mining: Collation, storage and analysis of text information and massive datasets ("Big Data") using natural language processing, pattern matching and machine learning techniques;
- Information Security: Developing methods to better understand the behaviour, spread and evolution of malicious software, informing policy requirements, and building secure information sharing technology;
- Distributed systems: Building secure and distributed information sharing and retrieval systems.