Publications
Published/ To appear
Ofori-Boateng D., Dominguez I.S., Akcora C., Kantarcioglu M., Gel Y.R. (2021) Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks. In: Oliver N., Pérez-Cruz F., Kramer S., Read J., Lozano J.A. (eds) Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2021. Lecture Notes in Computer Science, vol 12975. Springer, Cham. https://doi.org/10.1007/978-3-030-86486-6_48
Bush, B., Chen, Y., Ofori-Boateng, D., Chen, Y., and Gel, Y. R., “Topological machine learning methods for power system responses to contingencies”. Proceedings of the Innovative Applications of Artificial Intelligence (IAAI) Conference. 2021.
Ofori-Boateng, D., Gel, Y. R., and Cribben, I. (2021), “Nonparametric Anomaly Detection on Time Series of Graphs”, Journal of Computational and Graphical Statistics, pp.1-26. DOI: 10.1080/10618600.2020.1844214.
Ofori-Boateng, D., Dey, A. K., Gel, Y. R., and Poor, H. V. (2020) “Graph-Theoretic Analysis of Power Grid Resilience”, Book Chapter, Advanced Data Analytics for Power Systems, Cambridge University Press, To appear.
Li, B., Ofori-Boateng, D., Gel, Y.R. and Zhang, J., (2020). “A Hybrid Approach for Transmission Grid Resilience Assessment Using Reliability Metrics and Power System Local Network Topology”, Sustainable and Resilient Infrastructure, pp.1-16 . DOI: 10.1080/23789689.2019.1708182
Ofori-Boateng, D., Dey, A. K., Gel, Y. R., Li, B., Zhang, J., and Poor, H. V. (2019) “Assessing The Resilience Of The Texas Power Grid Network”, Proc. 2019 IEEE Data Science Workshop, Minneapolis, MN, USA, pp. 280-284. DOI: 10.1109/DSW.2019.8755787
Submitted/ Work-in-progress
Ofori-Boateng, D., Cribben, I., and Gel, Y. R., “Detecting Anomalies in Network Higher Order Structures with Generalized Tensor Spectrum”, In Progress.