Dr Basem Suleiman
School of Computer Science
Dr. Suleiman is an accomplished educator, researcher, and industry collaborator with a Ph.D. in Computer Science from the University of New South Wales (UNSW), Sydney, Australia. With wealth of experience spanning academia and industry, Dr. Suleiman has contributed to the design and development of cutting-edge software systems at world-class organizations, including SAP, CSIRO’s Data61, and leading universities such as UNSW and the University of Sydney. He has collaborated extensively with academics and industry professionals across multiple continents to drive innovation in software engineering and applied AI.
His research focuses onAI-driven Software Services, with applications spanning education, healthcare, and government digital services. He secured multiple research grants, published in prestigious conferences and journals, and supervised numerous honours, PhD, and capstone research students.
As Deputy Director of External Engagement at the school of Computer Science, Dr. Suleimaninitiated collaborations between academia, industry, and research institutes. Heactively facilitates project opportunities for students through industry partnerships and assist in program reviews and course development.
Dr. Suleiman is committed to excellence in teaching and curriculum innovation. His teaching philosophy is rooted in problem-solving and research-based strategies, ensuring students acquire the critical skills needed to tackle real-world challenges.
- Web Information Services including Human-Machine Interaction Services, Recommender Services and Service Personalisation.
- Education Technologies including personalised learning, inclusive and equitable learning
- Applied AI including GenAI, Machine Learning, Deep Learning and Predictive Analytics
Research Supervision:
- Arthur Chen,Ph.D.(2025 – 2028),Primary Supervisor.Leveraging Large Language Models for Enhanced Experience in Educational Domains. University of New South Wales
- Minhua Zhou,Ph.D.(2025 – 2028),Joint Supervisor.Thesis: Microservice Sharing, Validation and Development for Collaborative Analytics. University of New South Wales
- Yuyan Wang,Ph.D.(2025 – 2028),Joint Supervisor.Thesis: Analyzing the Impact of ESG Using AI Methods. University of New South Wales
- Piyavachara Nacchanandana,M.Phil(2024 – 2026),Primary Supervisor. Thesis: Design Patterns for Fine-tunning Large Language Models for Teaching and Learning. University of New South Wales.
- Ali Alyatimi,Ph.D.(2023 – 2026),External Supervisor.Thesis: Multi-Omics Data Integration for Disease Diagnosis Using Deep Learning.University of Sydney
- Muhammad Iqbal,Ph.D.(2023 – 2026),External Supervisor.Thesis:Collaborative Classification for Rare Diseases Across Distributed Healthcare Institutes. University of Sydney
- Aya Tafech,Ph.D.part-time (2022 – 2028),Joint Supervisor. Thesis: Anomaly Detection and Categorisation in Financial Regulatory Reporting. University of New South Wales
- MingqinYu,Ph.D.(2021 – 2024),Joint Supervisor.Thesis:an ESG metrics management system for sustainable financial applications.
- Lakshmi Sankaran,Ph.D.(2020 – 202),External Supervisor. Thesis: Elastic Intelligent Cloud Architecture for Academic Community Infrastructure. Christ University.
I am driven by the vision of creating intelligent, human-centered AI solutions that enhance the way we interact with digital services, learn, and make decisions. My research explores how Applied AI, Generative AI, and Machine Learning can revolutionize Web Information Services, Human-Machine Interaction, and Education Technologies, making them more adaptive, inclusive, and impactful.
Imagine a world where AI-driven web services understand user needs, personalize experiences, and enhance decision-making—where recommender systems go beyond predicting preferences to proactively guide users in meaningful ways.I inspire ideas from real-world problems and needs with the goal to develop world-class solutions that contribute to making positive impact on societies and environment. My research is motivated by designing and developing innovative AI models for the web including human-centered services, human-machine interaction services, recommender services, service personalization. I am also interested in applying the research outcomes to important fields such as education, healthcare and government.In recent years, I have designed, developed, and evaluated innovative AI models, algorithms, and software/information systems to address critical challenges in web information services, recommendation service and personalisation, and human-machine interaction using Machine and Deep Learning, and recently Large Language Models (LLMs).
I welcome industry collaborations, interdisciplinary partnerships, and ambitious PhD candidates to join me in exploring the potential of intelligent systems that shape the future of digital services and learning.
- ACM Professional member – ACM
- IEEE Professional member – IEEE Society
- IEEE Technical Committee on Services Computing – IEEE TCS
- Professional member – the System Administrators Group of Australia (SAGE‐AU)
- Invited keynote speaker – 2022 International Conference on Software Engineering and Information Technology (ICoSEIT)
- Runner up Best Paper Award, AI-enabled Process Automation workshop (ICSOC conference, 2023)
- Dean’s Commendation for achieving Outstanding University Satisfactory Survey (students teaching feedback) for courses I taught and coordinatedincluding COMP5347 (Web Application Development), COMP9412 (Agile Software Development Practices), INFO4444 (Computing 4 Innovation), COMP5651 (Software Engineering Project)
- Invited guest lecture (2014), Technology Innovation and Management, School of Systems, Management and Leadership, University of Technology Sydney, Australia
- Invited guest lecture (2012), Elasticity of Cloud-based Applications, School of Computer Science & Engineering, University of New South Wales
- Invited to SAP Product Development Teams in Germany and Bulgaria (2011), presented roadmap for enabling cloud elasticity and auto-scaling for SAP enterprise applications
- Invited Research Visit (2009 & 2010), research collaboration, National Institute of Informatics (NII)
India | (Christ University) PhD supervision |
Publications
Journals
- Anaissi, A., Suleiman, B., Alyassine, W., Zandavi, S. (2023). A fast parallel tensor decomposition with optimal stochastic gradient descent: an application in structural damage identification. International Journal of Data Science and Analytics. [More Information]
- Anaissi, A., Suleiman, B., Alyassine, W. (2023). Personalised federated learning framework for damage detection in structural health monitoring. Journal of Civil Structural Health Monitoring, 13(2023-03-02 00:00:00), 295-308. [More Information]
- Sankaran, L., Saleema, J., Suleiman, B. (2023). Policies and metrics for schedulers in cloud data-centers using CloudSim simulator. International Journal of Data Science and Analytics. [More Information]
Conferences
- Osop,, H., Suleiman, B., Lakhdari, A. (2022). 14 Days Later: Temporal Topical Shifts in Covid-19 Related Tweets After Pandemic Declaration. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), : Springer Verlag.
- Anaissi, A., Suleiman, B. (2022). A Personalized Federated Learning Algorithm for One-Class Support Vector Machine: An Application in Anomaly Detection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), : Springer Verlag.
- Sankaran,, L., Saleema,, J., Suleiman, B. (2022). Analysis of Workloads for Cloud Services. Proceedings - 2022 IEEE/ACIS 7th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2022, : SAGE Publications Inc.
2023
- Anaissi, A., Suleiman, B., Alyassine, W., Zandavi, S. (2023). A fast parallel tensor decomposition with optimal stochastic gradient descent: an application in structural damage identification. International Journal of Data Science and Analytics. [More Information]
- Anaissi, A., Suleiman, B., Alyassine, W. (2023). Personalised federated learning framework for damage detection in structural health monitoring. Journal of Civil Structural Health Monitoring, 13(2023-03-02 00:00:00), 295-308. [More Information]
- Sankaran, L., Saleema, J., Suleiman, B. (2023). Policies and metrics for schedulers in cloud data-centers using CloudSim simulator. International Journal of Data Science and Analytics. [More Information]
2022
- Osop,, H., Suleiman, B., Lakhdari, A. (2022). 14 Days Later: Temporal Topical Shifts in Covid-19 Related Tweets After Pandemic Declaration. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), : Springer Verlag.
- Anaissi, A., Suleiman, B. (2022). A Personalized Federated Learning Algorithm for One-Class Support Vector Machine: An Application in Anomaly Detection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), : Springer Verlag.
- Ahamed, F., Farid, F., Suleiman, B., Jan, Z., Wahsheh, L., Shahrestani, S. (2022). An Intelligent Multimodal Biometric Authentication Model for Personalised Healthcare Services. Future Internet, 14(8). [More Information]
2021
- Zhou, B., Suleiman, B., Yaqub, W. (2021). Aesthetic-Aware Recommender System for Online Fashion Products. 28th International Conference on Neural Information Processing, ICONIP 2021, Cham: Springer Science+Business Media. [More Information]
- Suleiman, B., Lu, K., Chan, H., Alibasa, M. (2021). DeepPatterns: Predicting Mobile Apps Usage from Spatio-Temporal and Contextual Features. 19th International Conference on Service-Oriented Computing (ICSOC 2021), Cham: Springer Nature. [More Information]
- Suleiman, B., Anaissi, A., Zhan, B., Alibasa, M. (2021). Intelligent Failure Prediction in Industrial Vehicles. 2021 International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
2020
- Lakhdari, A., Bouguettaya, A., Mistry, S., Neiat, A., Suleiman, B. (2020). Elastic composition of crowdsourced IoT energy services. 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2020, New York: Association for Computing Machinery (ACM). [More Information]
- Anaissi, A., Suleiman, B., Zandavi, S. (2020). Online Tensor Decomposition with optimized Stochastic Gradient Descent: An Application in Structural Damage Identification. 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020), Canberra: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
2013
- Suleiman, B., Venugopal, S. (2013). Modeling performance of elasticity rules for cloud-based applications. 17th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2013, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers Inc. [More Information]
2012
- Suleiman, B. (2012). Elasticity economics of cloud-based applications. 2012 IEEE 9th International Conference on Services Computing (SCC 2012), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
- Suleiman, B., Sakr, S., Jeffery, R., Liu, A. (2012). On understanding the economics and elasticity challenges of deploying business applications on public cloud infrastructure. Journal of Internet Services and Applications, 3(2), 173-193. [More Information]
- Suleiman, B., Sakr, S., Venugopal, S., Sadiq, W. (2012). Trade-off analysis of elasticity approaches for cloud-based business applications. The 13th International Conference on WEb Information System Engineering (WISE 2012), Heidelberg: Springer Verlag. [More Information]
2011
- Roy, M., Suleiman, B., Weber, I. (2011). Facilitating enterprise service discovery for non-technical business users. 8th International Conference on Service Oriented Computing ICSOC 2010, Germany: Springer. [More Information]
- Suleiman, B., Da Silva, C., Sakr, S. (2011). One size does not fit all: A group-based service selection for web-based business processes. 25th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2011, Washington, D.C., United States: IEEE Computer Society. [More Information]
- Roy, M., Suleiman, B., Schmidt, D., Weber, I., Benatallah, B. (2011). Using SOA governance design methodologies to augment enterprise service descriptions. 23rd International Conference on Advanced Information Systems Engineering, CAiSE 2011, Berlin, Germany: Springer. [More Information]