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Dr Lowri Williams
(she/her)
Lecturer in Cybersecurity
School of Computer Science and Informatics
- WilliamsL10@cardiff.ac.uk
- +44 29225 14919
- Abacws, Room 5.02, Senghennydd Road, Cathays, Cardiff, CF24 4AG
- Welsh speaking
Overview
A research data scientist with 4 years of experience in academic research and 2 years in industry-based collaborations supporting small-medium businesses with novel data science solutions.
Research areas and interests: natural language processing, computational linguistics, data mining, text mining, sentiment analysis, language resources, machine learning, feature engineering, classification, classification schemes, data science, data annotation, crowdsourcing.
Collaborated with multidisciplinary experts, as well as applying expertise within different academic disciplines such as cybersecurity, to present research outputs and findings within several reputable academic journals. This shows creativity within my research by using state of the art technologies to tackle complex research problems.
Maintainter of Cardiff University's Cyber Events - a website which allows staff and students to keep up to date with the latest cybersecurity events and competitions at Cardiff University.
Publication
2024
- Williams, L., Anthi, E. and Burnap, P. 2024. Comparing hierarchical approaches to enhance supervised emotive text classification. Big Data and Cognitive Computing 8(4) (10.3390/bdcc8040038)
- Williams, L., Anthi, E., Cherdantseva, Y. and Javed, A. 2024. Leveraging gamification and game-based learning in cybersecurity education: Engaging and inspiring non-cyber students. Journal of The Colloquium for Information Systems Security Education
2021
- Anthi, E., Williams, L., Javed, A. and Burnap, P. 2021. Hardening machine learning Denial of Service (DoS) defences against adversarial attacks in IoT smart home networks. Computers and Security 108, article number: 102352. (10.1016/j.cose.2021.102352)
- Anthi, E., Williams, L., Rhode, M., Burnap, P. and Wedgbury, A. 2021. Adversarial attacks on machine learning cybersecurity defences in industrial control systems. Journal of Information Security and Applications 58, article number: 102717. (10.1016/j.jisa.2020.102717)
- Anthi, E., Williams, L., Burnap, P. and Jones, K. 2021. A three-tiered intrusion detection system for Industrial Control Systems (ICS). Journal of Cybersecurity 7(1), article number: tyab006. (10.1093/cybsec/tyab006)
2020
- Spasic, I., Williams, L. and Buerki, A. 2020. Idiom–based features in sentiment analysis: cutting the Gordian knot. IEEE Transactions on Affective Computing 11(2) (10.1109/TAFFC.2017.2777842)
2019
- Williams, L., Arribas-Ayllon, M., Artemiou, A. and Spasic, I. 2019. Comparing the utility of different classification schemes for emotive language analysis. Journal of Classification 36(3), pp. 619-648. (10.1007/s00357-019-9307-0)
- Anthi, E., Williams, L., Malgorzata, S., Theodorakopoulos, G. and Burnap, P. 2019. A supervised intrusion detection system for smart home IoT devices. IEEE Internet of Things 6(5), pp. 9042-9053. (10.1109/JIOT.2019.2926365)
2017
- Williams, L. 2017. Pushing the envelope of sentiment analysis beyond words and polarities. PhD Thesis, Cardiff University.
2015
- Williams, L., Bannister, C., Arribas-Ayllon, M., Preece, A. and Spasic, I. 2015. The role of idioms in sentiment analysis. Expert Systems with Applications 42(21), pp. 7375-7385. (10.1016/j.eswa.2015.05.039)
Erthyglau
- Williams, L., Anthi, E. and Burnap, P. 2024. Comparing hierarchical approaches to enhance supervised emotive text classification. Big Data and Cognitive Computing 8(4) (10.3390/bdcc8040038)
- Williams, L., Anthi, E., Cherdantseva, Y. and Javed, A. 2024. Leveraging gamification and game-based learning in cybersecurity education: Engaging and inspiring non-cyber students. Journal of The Colloquium for Information Systems Security Education
- Anthi, E., Williams, L., Javed, A. and Burnap, P. 2021. Hardening machine learning Denial of Service (DoS) defences against adversarial attacks in IoT smart home networks. Computers and Security 108, article number: 102352. (10.1016/j.cose.2021.102352)
- Anthi, E., Williams, L., Rhode, M., Burnap, P. and Wedgbury, A. 2021. Adversarial attacks on machine learning cybersecurity defences in industrial control systems. Journal of Information Security and Applications 58, article number: 102717. (10.1016/j.jisa.2020.102717)
- Anthi, E., Williams, L., Burnap, P. and Jones, K. 2021. A three-tiered intrusion detection system for Industrial Control Systems (ICS). Journal of Cybersecurity 7(1), article number: tyab006. (10.1093/cybsec/tyab006)
- Spasic, I., Williams, L. and Buerki, A. 2020. Idiom–based features in sentiment analysis: cutting the Gordian knot. IEEE Transactions on Affective Computing 11(2) (10.1109/TAFFC.2017.2777842)
- Williams, L., Arribas-Ayllon, M., Artemiou, A. and Spasic, I. 2019. Comparing the utility of different classification schemes for emotive language analysis. Journal of Classification 36(3), pp. 619-648. (10.1007/s00357-019-9307-0)
- Anthi, E., Williams, L., Malgorzata, S., Theodorakopoulos, G. and Burnap, P. 2019. A supervised intrusion detection system for smart home IoT devices. IEEE Internet of Things 6(5), pp. 9042-9053. (10.1109/JIOT.2019.2926365)
- Williams, L., Bannister, C., Arribas-Ayllon, M., Preece, A. and Spasic, I. 2015. The role of idioms in sentiment analysis. Expert Systems with Applications 42(21), pp. 7375-7385. (10.1016/j.eswa.2015.05.039)
Gosodiad
- Williams, L. 2017. Pushing the envelope of sentiment analysis beyond words and polarities. PhD Thesis, Cardiff University.
