Dalian University of Technology | China
Author Profile
Google Scholar
Early Academic Pursuits
Faisal Alshami’s academic journey reflects a deep commitment to software engineering and technological innovation. He began his undergraduate studies at Sana’a University, Yemen, earning a BSc in Network Technology and Computer Security (2008–2012). His undergraduate thesis, “General Management System for Plant Protection,” showcased his early ability to integrate security and system management using ASP.NET, C#, and VPN with OSPF protocols, signaling his strong foundation in both networking and software development. Building on this groundwork, Faisal pursued a Master’s in Software Engineering at Northeastern University, China (2019–2022), where he specialized in advanced machine learning techniques. His master’s thesis, “Design and Implementation of Web API Recommendation System Based on Deep Learning,” utilized CNN, BLSTM, K-modes, and Word2Vec, demonstrating his growing expertise in AI-driven software solutions. Currently, Faisal is advancing his academic pursuits with a PhD in Software Engineering at Dalian University of Technology, China, focusing on federated learning, distributed systems, blockchain, edge computing, and graph neural networks (GNNs).
Professional Endeavors
Alongside his academic progression, Faisal has accumulated over 5 years of professional experience in the software and networking industry. His early career as a VoIP Engineer/Developer at Communication Services Company (2013–2015) allowed him to develop communication APIs and optimize large-scale systems. As a Network Manager and Systems Engineer at EliteTecs (2015–2016), he designed high-reliability networks using advanced protocols such as OSPF, EIGRP, and WiMAX, showcasing his expertise in secure and resilient infrastructures. His role as Full-Stack Developer and DevOps Lead at Almorisi Exchange Company (2016–2018) highlighted his ability to manage mission-critical systems with real-time performance and security. Here, Faisal excelled in building scalable architectures, simulation frameworks, and automated DevOps pipelines, which contributed to operational excellence.
Contributions and Research Focus
Faisal’s research is strategically positioned at the intersection of distributed systems, intelligent computing, and aerospace applications. His focus includes:
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Federated learning and secure communication for multi-agent systems such as satellite constellations.
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Edge computing and real-time distributed systems tailored for resource-constrained environments.
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Robust machine learning frameworks for aerospace, automation, and high-reliability embedded systems.
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Blockchain integration with AI to enhance security in data networks.
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Simulation and testing methodologies to ensure fault tolerance in mission-critical software.
This body of research reflects his ambition to address pressing challenges in space exploration, aerospace engineering, and advanced communication networks.
Impact and Influence
Faisal’s impact lies in bridging the gap between theory and applied innovation. His academic research is not confined to publications alone but extends into real-world applications in secure communications, high-availability systems, and intelligent software architectures. By combining his professional experience with cutting-edge research, Faisal has influenced the fields of network security, distributed computing, and AI-driven system optimization, making his contributions valuable to both academia and industry.
Academic Cites
His work has strong potential for academic citations due to its interdisciplinary nature—linking software engineering, AI, networking, and aerospace technologies. His focus on federated learning, blockchain, and edge computing positions his research at the forefront of emerging scholarly and industrial discussions, ensuring that his publications will attract citations in journals focusing on AI, distributed systems, cybersecurity, and aerospace software engineering.
Legacy and Future Contributions
Faisal Alshami is on a trajectory to build a lasting legacy in intelligent, secure, and scalable software engineering systems. His research is particularly impactful in aerospace applications and secure communications, areas that are becoming increasingly vital in a digital and space-driven era. As he progresses with his doctoral research, Faisal is expected to contribute significantly to the development of resilient federated learning frameworks, advanced distributed architectures, and mission-critical simulations. His blend of academic depth and industry experience ensures that his future work will leave a lasting influence on next-generation computing systems and aerospace engineering technologies.
Other Notable Highlights
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Certifications: Faisal holds multiple certifications, including Neural Networks & Deep Learning (DeepLearning.AI), CCNP, CCNA, and advanced language certifications (Chinese HSK4, English YALI).
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Training: He gained practical exposure at NEUSOFT Project Training, where he contributed to developing the Borrow-Seller System (BSS) using Java, Spring Boot, Vue.js, and Android Studio.
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Core Competencies: His expertise spans software architecture, DevOps, distributed systems, full-stack development, secure networking, and agile collaboration.
Conclusion
In conclusion, Faisal Alshami is an emerging leader in the domain of software engineering, distributed systems, and intelligent computing. His academic journey, professional experiences, and research pursuits demonstrate a rare combination of technical mastery, innovation, and practical problem-solving skills. With his ongoing doctoral work and focus on future technologies such as federated learning, blockchain, and aerospace applications, Faisal is poised to make significant contributions that will influence both academia and industry for years to come.
Notable Publications
"A detailed analysis of benchmark datasets for network intrusion detection system"
- Author: M Ghurab, G Gaphari, F Alshami, R Alshamy, S Othman
- Journal: Asian Journal of Research in Computer Science
- Year: 2021
"Intrusion detection model for imbalanced dataset using SMOTE and random forest algorithm"
- Author: International Conference on Advances in Cyber Security
- Journal: Kybernetes
- Year: 2021