Basit Qureshi
Prince Sultan University, University of Bradford, Florida Atlantic University, Ohio University
Research areas: Computer Science · Computer Networks and Communications · IoT and Edge/Fog Computing · Cloud Computing and Resource Management · Robotics and Automated Systems
0000-0001-7389-519X
About
Dr. Basit Qureshi specializes in Cloud computing with a focus on performance issues in Energy-aware and Green-computing, integrating Cloud and Internet-of-things applications in the context of smart cities. He is involved in various research activities. He has over 100 publications in peer-reviewed International journals and conferences. He received the best paper award at the 6th IEEE/IEFP Trustcom 2010 held in Hong Kong. He has served as a program committee member and organizing committee member of many local and international conferences. He has been the chair and co-chair of the Symposium on Data Mining Applications, now the International Conference on Data Science and Machine Learning (CDMA); held bi-annually in Saudi Arabia since 2010. Moreover, he has reviewed research works for journals such as IEEE Transactions on Mobile Computing, IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Cloud Computing, IEEE Transactions on Vehicular Technology, IEEE Access, Elsevier Computer Communications, Future Generation Computer Systems, Ad-Hoc Networks and Springer Journal of Supercomputing. He has been involved in various funded research projects. These projects were funded by King Abdulaziz City for Science and Technology as well as Industrial funds from Saudi Telecom, Al-Elm, Machinestalk, etc with over 2 million SAR in research grants. Previously, he served as the Director of Prince Megrin Data Mining Center and the Chair of the Computer Science Department at Prince Sultan University.
He has been the organizing chair for the Annual ACM Programming Jam competitions since 2014. He has been the mentor for students in the IEEE Extreme competitions since 2013 proctoring various teams. He received numerous awards for student activities and participation in various competitions at National and International stages.
Dr. Qureshi is with the College of Computer & Information Science at Prince Sultan University. He is a Full Professor in the Department of Computer Science. He received his Ph.D. degree in Computer Science from the University of Bradford in the year 2011. Prior to that, he received his Master of Science degree in Computer Science from Florida Atlantic University in 2002 and his Bachelor of Science degree in Computer Science from Ohio University, OH USA in 2000. He is a Fellow of the Higher Education Academy (UK). He is also a senior member of IEEE, IEEE Computer Society, and IEEE Communication Society.
Employment
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Prince Sultan University Professor2024 - Present
Education
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University of Bradford PhD Computer Science? - 2011
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Florida Atlantic University Master of Science in Computer Science? - 2002
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Ohio University Bachelor of Science in Computer Science? - 2000
Projects & Funding
Projects & funding information is unavailable.
Publications (160)
- Boosting Code Retrieval Performance on Q&A Sites with Neural Mutual Attentions Save
- Carbon-aware decentralized dynamic task offloading in MIMO-MEC networks via multi-agent reinforcement learning Save
- Federated learning for intelligent transportation systems: Emerging trends, challenges and future directions Save
- TAWB-SFL: Trust-Aware Blockchain-Orchestrated Split Federated Learning for Intrusion Detection in 6G Healthcare IoT Save
- 8th International Conference on Data Science and Machine Learning Applications (CDMA2025) Save
- A New Distributed Approach to Leveraging AI for Sustainable Healthcare in Smart Cities Save
- An Efficient and Hybrid Deep Learning-Driven Model to Enhance Security and Performance of Healthcare Internet of Things Save
- Comparative Analysis of Federated Learning Techniques in Big Data-Driven Intelligent Transportation Systems Save
- IMPACT-TB: Integrated Medical Imaging and AI for Precise Tuberculosis Detection Save
- Machine learning-driven Diabetes Health Tracer (DHT): Optimizing prognosis using RaSK_GraDe and RaSK_GraDeL models Save
- Review on Federated Learning for digital transformation in healthcare through big data analytics Save
- Synchronizing smart city nodes using Skew Integrated Timestamp (SIT) Save
- Investigating the impact of data heterogeneity on the performance of federated learning algorithm using medical imaging Save
- Adaptive Multi-Criteria Selection for Efficient Resource Allocation in Frugal Heterogeneous Hadoop Clusters Save
- Computational Approach for Automated Segmentation and Classification of Region of Interest in Lateral Breast Thermograms Save
- Optimizing Hadoop Scheduling in Single-Board-Computer-Based Heterogeneous Clusters Save
- Soil texture analysis using controlled image processing Save
- Humans are still better than ChatGPT: Case of the IEEEXtreme competition Save
- ChatGPT in Computer Science Curriculum Assessment: An analysis of Its Successes and Shortcomings Save
- Ensemble learning for multi-class COVID-19 detection from big data Save