Dr. Brian Keegan
brian.x.keegan@tudublin.ie
Co-founder & Director of the Applied Social Computing Research group
Head of Undergraduate Studies in Computer Science, TU Dublin
Dr. Brian Keegan is a Senior lecturer at TU Dublin School of Computer Science and a Founding member of ASCNet. Brian’s teaching covers undergraduate and post graduate courses. Teaching duties include network engineering, Cybersecurity, Systems Administration, and Internet of Things. Brian supervises PhD students whose research includes networking, security, algorithm design, and Machine Learning. Brian has the ability to work within the disciplines of computer science and engineering providing unique subject matter expertise that can be applied to most ICT initiatives. Brian has been instrumental in starting a new research group, Applied Social Computing Network (ASCNet) with the aim of engaging in societal challenges that can be addressed through computing technology. Brian is a Senior Member of IEEE and an EU Expert Evaluator on Future and Emerging Technologies.
Dr. Brian Keegan has a background in Electrical and Electronic Engineering with a PhD specialisation in Wireless Networks completed in 2010 at DIT. Brian also holds an M.Phil and B.Eng in Electrical and Electronic Engineering as we as a Post Graduate Diploma in Third Level Teaching and Learning.
Brian has worked for Oracle (Sun Microsystems) as software engineer and release lead as well as working for Cisco Systems San Jose as software developer and test engineer. Prior to this Brian had worked as an electrical building services engineer. Brian’s has been involved with academic teaching since 1998 and is currently a Senior Lecturer with TU Dublin Computer Science. He has worked for the EU commission as an Expert Evaluator since 2016. In 2018 Brian was awarded IEEE Senior Membership.
Brian’s main areas of research include Networking, Internet of Things, Cybersecurity, Machine Learning, AI, and algorithm design. In addition Brian carries out research in teaching and learning for STEM.
Current Projects
- GETM3 – Horizon 2020 – €950,000
- Global Innovation Teams – Erasmus+ – €300,000
Previous Projects
HubLinked Knowledge Alliance – Erasmus+ – €1,000,000
Quality Blended Learning – Erasmus+ – €200,000
ASCNet (Applied Social Computing Network) – Founding member of a this research group which spans multiple disciplines and countries
Applied Intelligence Research Centre – Principal Investigator
ML-Labs SFI Centre for Research Training in Machine Learning
IEEE Senior Membership
Informatics Europe Member
Brian was a PI after successfully acquiring funding for an ERASMUS+ Project, FOSS4SMEs. He formed part of a collaborative project with members from academia and industry in Greece, Germany, Sweden, Italy and the UK.
Queiroz, A. L., Mckeever, S., and Keegan, B. (2019). Eavesdropping hackers: Detecting software vulnerability communication on social media using text mining. In The 4th International Conference on Cyber-Technologies and Cyber-Systems, pages 41–48.
Queiroz, A. L., Mckeever, S., and Keegan, B. (2019). Detecting hacker threats: Performance of Word and Sentence Embedding models in identifying hacker communications. In The 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, volume 2563, pages 116–127.
Queiroz, A. L., Keegan, B., and Mckeever, S. (2020). Moving Targets: Addressing Concept Drift in Supervised Models for Hacker Communication Detection. In International Conference on Cyber Security and Protection of Digital Services (Cyber Security), pages 1–7.
Lima, A. Q. and Keegan, B. (2020). Chapter 3 – Challenges of using machine learning algorithms for cybersecurity: a study of threat-classification models applied to social media communication data. In Benson, V. and Mcalaney, J., editors, Cyber Influence and Cognitive Threats, pages 33–52.
Xinlu, L., Keegan, B. and Japhet, F. Ant colony clustering routing protocol for optimization of large scale wireless sensor networks,14th Information Technology and Telecommunications Conference (IT&T 2015), Dublin, Ireland,2015.10.29-10.30.
Xinlu Li, Brian Keegan, and Fredrick Mtenzi. Clustering Opportunistic Ant-based Routing Protocol for Wireless Sensor Networks, 7th International Conference on Computer Engineering and Networks. Shanghai, China, 2017.7.22-7.23.
Andrei Queiroz, Brian Keegan, and Fredrick Mtenzi. Predicting software vulnerability using security discussion in social media.. In European Conference on Information Warfare and Security, ECCWS, pages 628–634, Dublin, Ireland, June 2017.
Xinlu Li, Brian Keegan, and Fredrick Mtenzi. Energy Efficient Load Balancing Ant Based Routing Algorithm for Wireless Sensor Networks. International Journal of Distributed Sensor Networks(Peer Review in Process).