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Banziger, R.B., Basukoski, A. and Chaussalet, T.J. 2018. Discovering Business Processes in CRM Systems by leveraging unstructured text data. The 4th IEEE International Conference on Data Science and Systems (DSS-2018). Exeter, UK 28 - 30 Jun 2018 IEEE . https://doi.org/10.1109/HPCC/SmartCity/DSS.2018.00257

Basso, A., Bolotov, A., Basukoski, A., Getov, Vladimir, Henrio, L. and Urbanski, M. 2006. Specification and verification of reconfiguration protocols in grid component systems. CoreGRID. https://doi.org/CoreGRIDTechnicalReportNumberTR-0042

Ogunbiyi, O., Basukoski, A. and Chaussalet, T.J. 2022. Comparative analysis of clustering-based remaining-time predictive process monitoring approaches. International Journal of Business Process Integration and Management. 10 (3/4), pp. 230-241. https://doi.org/10.1504/IJBPIM.2021.124023

Chishti, I., Basukoski, A., Chaussalet, T.J. and Beeknoo, N. 2018. Transformation of UML Activity Diagram for Enhanced Reasoning. Future Technologies Conference 2018. Vancouver, Canada 13 - 14 Nov 2018 Springer. https://doi.org/10.1007/978-3-030-02683-7_33

Chishti, I., Basukoski, A. and Chaussalet, T.J. 2018. Modeling Patient Flows: A Temporal Logic Approach. Journal On Computing. 6 (1) 1516. https://doi.org/10.5176/2251-3043_6.1.107

Chishti, I., Basukoski, A. and Chaussalet, T.J. 2017. Modeling and Optimizing Patient Flows. 8th Annual International Conference on ICT: Big Data, Cloud & Security. Singapore 21 - 22 Aug 2017 Global Science & Technology Forum. https://doi.org/10.5176/2251-2136_ICT-BDCS17.52

Ogunbiyi, N., Basukoski, A. and Chaussalet, T.J. 2020. Investigating Social Contextual Factors in Remaining-Time Predictive Process Monitoring—A Survival Analysis Approach. Algorithms. 13 (11), p. e267. https://doi.org/10.3390/a13110267

Bolotov, A. and Basukoski, A. 2004. A clausal resolution method for branching-time logic ECTL+. in: Combi, C. (ed.) 11th International Symposium on Temporal Representation and Reasoning: (TIME 2004), Tatihou, Normandie, France, 1-3 July 2004 IEEE . pp. 140-147

Ogunbiyi, O., Basukoski, A. and Chaussalet, T.J. 2020. Investigating the Diffusion of Workload-Induced Stress—A Simulation Approach. Information. 12 (1) 11. https://doi.org/10.3390/info12010011

Ogunbiyi, O., Basukoski, A. and Chaussalet, T.J. 2021. An Exploration of Ethical Decision Making with Intelligence Augmentation. Social Sciences. 10 (2) 57. https://doi.org/10.3390/socsci10020057

Bolotov, Alexander 2022. On the Expressive Power of the Normal Form for Branching-Time Temporal Logics. Electronic Proceedings in Theoretical Computer Science. 358, pp. 254-269. https://doi.org/10.4204/eptcs.358.19

Bolotov, A. and Gorchakov, A. 2018. Tuning Natural Deduction Proof Search by Analytic Methods. The 25th Workshop on Automated Reasoning: Bridging the Gap between Theory and Practice. University of Cambridge Apr 2018 University of Cambridge.

Bolotov, A., Grigoriev, O. and Shangin, V. 2006. Natural deduction calculus for computation tree logic. in: IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing (JVA'06) Los Alamitos, USA IEEE . pp. 175-183

Basso, A. 2010. Integrating formal reasoning into component-based approach to reconfigurable distributed systems. PhD thesis University of Westminster School of Electronics and Computer Science https://doi.org/10.34737/90499

Ogunbiyi, Oluniyi 2022. Contextual and Ethical Issues with Predictive Process Monitoring. PhD thesis University of Westminster School of Computer Science and Engineering https://doi.org/10.34737/vqy62

Chishti, I. 2019. A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows. PhD thesis University of Westminster School of Computer Science and Engineering https://doi.org/10.34737/qy760

Bolotov, A. (ed.) 2014. Proceedings of the Joint Automated Reasoning Workshop and Deduktionstreffen: As part of the Vienna Summer of Logic – IJCAR 23-24 July 2014. IJCAR.

Protopsaltis, A. 2006. Reading in Web-based hypertexts: cognitive processes strategies and reading goals. PhD thesis University of Westminster School of Electronics and Computer Science https://doi.org/10.34737/92701

Mesgarpour, M. 2017. Predictive Risk Modelling of Hospital Emergency Readmission, and Temporal Comorbidity Index Modelling Using Machine Learning Methods. PhD thesis University of Westminster Computer Science https://doi.org/10.34737/q3031