Issa Qiqieh
Al-Balqa' Applied University Faculty of Engineering, Newcastle University, Yarmouk University Hijjawi Faculty for Engineering Technology
Research areas: Engineering · Electrical and Electronic Engineering · Low-power high-performance VLSI design · Network Security and Intrusion Detection · VLSI and FPGA Design Techniques
0000-0003-1178-6478
About
Issa Qiqieh is currently an assistant professor at Al-Balqa Applied University, Jordan. He received his Ph.D. degree in computer and electrical engineering from the School of Engineering, Newcastle University, Newcastle upon Tyne, UK, in 2018 and his M.Sc. (with distinction) and B.Sc. degrees from Hijjawi Faculty of Engineering Technology, Yarmouk University, Jordan, in 2007 and 2005, respectively. He has been working as a full-time lecturer in the Faculty of Engineering at Al-Balqa Applied University from 2007 until now. He is also the author/co-author of 15+ IEEE/ACM/Elsevier journal and conference articles. His research interests include multi- and interdisciplinary environments involving error-resilient/approximate computing circuit design and related applications, power-adaptive and energy-efficient computing system design for intelligent embedded and IoT systems, research solutions in machine learning, cyber security and cloud computing, analytical models for sizing microgrids, energy management optimization in smart grids, and decreasing CO2 emissions using DQN models.
Employment
-
Al-Balqa' Applied University Faculty of Engineering Assistant Professor2018 - Present
-
Al-Balqa' Applied University Faculty of Engineering Full-time lecturer2007 - 2014
Education
-
Newcastle University Ph.D., School of Electrical and Electronic Engineering2014 - 2018
-
Yarmouk University Hijjawi Faculty for Engineering Technology M.Sc., Computer Engineering / Embedded Systems2005 - 2007
-
Yarmouk University Hijjawi Faculty for Engineering Technology B.S., Computer Engineering2000 - 2005
Projects & Funding
Projects & funding information is unavailable.
Publications (27)
- Securing Next-Generation Connected Healthcare: A Privacy-Preserving Explainable AI Framework for Consumer Electronics Save
- An intelligent cyber threat detection: A swarm-optimized machine learning approach Save
- A Hybrid Approach for Anomaly Detection with PCA-Driven CNNs Save
- A feature-learning-enabled malware analysis for enhanced IoT-centric cybersecurity Save
- An IoT Intrusion Detection Approach Based on Salp Swarm and Artificial Neural Network Save
- DNA cryptography based security framework for health-cloud data Save
- A Blended Deep Learning Intrusion Detection Framework for Consumable Edge-Centric IoMT Industry Save
- Battery management solutions for li-ion batteries based on artificial intelligence Save
- Design of cost-based sizing and energy management framework for standalone microgrid using reinforcement learning Save
- Fusion of deep learning based cyberattack detection and classification model for intelligent systems Save
- Machine learning techniques for automated policy violation reporting Save
- Optimized Machine Learning-Based Intrusion Detection System for Fog and Edge Computing Environment Save
- Run-time Configurable Approximate Multiplier using Significance-Driven Logic Compression Save
- An optimal pruning algorithm of classifier ensembles: dynamic programming approach Save
- Hashed Needham Schroeder Industrial IoT based Cost Optimized Deep Secured data transmission in cloud Save
- An integrated framework for sizing and energy management of hybrid energy systems using finite automata Save
- Significance-Driven Logic Compression for Energy-Efficient Multiplier Design Save
- Approximate adder segmentation technique and significance-driven error correction Save
- Configurable-Accuracy Approximate Adder Design with Light-Weight Fast Convergence Error Recovery Circuit Save
- Configurable-Accuracy approximate adder design with light-weight fast convergence error recovery circuit Save