Dr. Abdelmounaam Rezgui
Associate Professor
School Information Technology

Office
Old Union - OU 104
Office Phone
Email
- About
- Education
- Awards & Honors
- Research
Current Courses
379.001Advanced Computer Networks
276.001Data Communications
276.002Data Communications
386.001Introduction to Networking and Parallel and Distributed Computing
386.002Introduction to Networking and Parallel and Distributed Computing
444.001Data Analytics and Mining
276.003Data Communications
499.001Independent Research For The Master's Thesis
373.001Wide Area Network Infrastructures
Research Interests & Areas
Networking
Cloud computing
Big data
Social computing
Health informatics
IoT
Ph D Computer Science
Virginia Tech
Blacksburg, VA, USA
MS Computer Science
Purdue University
West Lafayette, IN, USA
IEEE Senior Member
IEEE
2023
Conference Proceeding
Alghatani, K., Rezgui, A., & Ammar , N. Predicting Out-of-Hospital Vital Sign Measurements through Deep Learning (2023)
Rezgui, A. Scaling Personalized Machine Learning through DTW Clustering: Predicting Glycemia Levels as an Example (2023)
Alshammari, A., & Rezgui, A. Better Edges not Bigger Graphs: An Interaction-Driven Friending Algorithm for the Next-Generation Social Networks. 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) (2020)
Alshammari, M., & Rezgui, A. POX-PLUS: An SDN Controller with Dynamic Shortest Path Routing. IEEE Conference on Cloud Networking (CloudNet) (2020)
Brighen, A., Slimani, H., Rezgui, A., & Kheddouci, H. A Distributed Large Graph Coloring Algorithm on Giraph. 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) (2020)
Journal Article
Brighen, A., Slimani, H., Rezgui, A., & Kheddouci, H. A new distributed graph coloring algorithm for large graphs. Cluster Computing/Spring US (2023)
Chaira, M., Aouag, S., Cherroun, H., Brik, B., & Rezgui, A. A decentralized blockchain-based authentication scheme for cross-communication in IoT networks. Cluster Computing/Springer US (2023): 1-19.
Lebal, A., Moussaoui, A., & Rezgui, A. Epilepsy-Net: attention-based 1D-inception network model for epilepsy detection using one-channel and multi-channel EEG signals. Multimedia Tools and Applications/Spring US 82.11 (2023)
Alghatani, K., Ammar, N., Rezgui, A., & Shaban-Nejad, A. Precision Clinical Medicine through Machine Learning: Using High and Low Quantile Ranges of Vital Signs for Risk Stratification of ICU Patients. IEEE Access/IEEE 10 (2022)
Lebal, A., Moussaoui, A., & Rezgui, A. Epilepsy-Net: attention-based 1D-inception network model for epilepsy detection using one-channel and multi-channel EEG signals. Multimedia Tools and Applications/Springer (2022): 1-23.
Technical Report
Rezgui, A. An SDN Testbed for ML Experimental Research in Chap.4: Potential Midscale Experimental Research Infrastructures. MERIF Workshop Report to NSF on Future Midscale Experimental Research Infrastructures (2020)
Presentations
Predicting Out-of-Hospital Vital Sign Measurements through Deep Learning. 3rd IEEE International Conference on ICT Solutions for eHealth (ICTS4eHealth). IEEE. (2023)
Scaling Personalized Machine Learning through DTW Clustering: Predicting Glycemia Levels as an Example. IEEE Conference on Big Data. IEEE. (2023)
Cloud-based Intelligent Remote Patient Monitoring. CloudTech 2020 : The 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications. (2020)
Towards Midscale Experimental Research Infrastructures that Support Intelligent, Self-configurable, Software-Defined Networks,. NSF Future Experimental Research Infrastructures Workshop. (2020)
Grants & Contracts
Cost-effective Road Maintenance through Machine Learning and Optimization Methods. Illinois Innovation Network. State. (2023)
Cost-effective Road Maintenance through ML and Optimization Method. SIT. Illinois State University. (2022)
Cloud-based Health Monitoring through Personalized Machine Learning. CAST. Illinois State University. (2021)
Scaling the Internet to the Things: Combining Named Data Networking and Software-Defined Networking to Support the Next 50 Billon IoT Devices. School of Information Technology. Illinois State University. (2021)