Agentic AI for networking
Autonomous AI agents for network orchestration, optimization, and control across wireless, edge, and 5G/6G systems under dynamic resource and communication constraints.
Researcher · Educator · Inventor
Abdullatif Albaseer, PhD
Intelligence belongs in the network.
Researcher working at the intersection of AI, autonomous networking, and cybersecurity.
My research focuses on designing distributed learning systems that coordinate across connected devices, adapt to constrained and unreliable networks, and improve the resilience and security of critical infrastructure.
01 / RESEARCHResearch impactIdeas translated into evidence.
70+peer-reviewed publications
20h-index
6granted US patents
HBKUPhD institution
Research agenda
Networks that learn, adapt, and defend.
Three connected lines of inquiry shape the work: intelligence inside the network, intelligence protecting the network, and intelligence distributed across the network.
Agentic AI for cybersecurity
Autonomous and collaborative AI agents for threat detection, adaptive defense, incident response, and resilient protection of IoT, smart grids, and critical infrastructure.
Secure autonomous networked systems
Trustworthy multi-agent intelligence for coordinating distributed devices and services, enabling secure collaboration, resilient decision-making, and reliable operation under network constraints.
Selected work
Recent research with a clear direction.
202520262026202620242026
IEEE Network Magazine
LLM-Driven Multi-Agent Architectures for Intelligent Self-Organizing Networks
IEEE Transactions on Network and Service Management
Incentive-Driven Honeypot Defense: A Multi-Agent DRL Framework for Securing Smart Grid Networks
IEEE Transactions on Consumer Electronics
Proactive Smart-Grid Defense: DRL-Powered Moving Target Defense Against False Data Injection Attacks
IEEE Transactions on Network and Service Management
DMGCRL: Dynamic Multi-Scale Graph Contrastive Representation Learning For Network Intrusion Detection
IEEE Transactions on Network and Service Management
FedPot: A Quality-Aware Collaborative and Incentivized Honeypot-Based Detector for Smart Grid Networks
IEEE Transactions on Machine Learning in Communications and Networking
Personalized Federated Learning with Adaptive Transformer Pruning and Hypernetwork-Driven Personalization in Wireless Networks
Trajectory
Research depth, built across institutions and systems.
Experience
Laboratory Manager
Hamad Bin Khalifa University
Postdoctoral Research Fellow
Hamad Bin Khalifa University
Visiting Scholar, Smart Grid Lab
Texas A&M University at Qatar
Graduate Research Assistant
Hamad Bin Khalifa University
Education
PhD in Computer Science and Engineering
Hamad Bin Khalifa University, Doha, Qatar
MSc in Computer Networks
King Fahd University of Petroleum and Minerals
BSc in Computer Science
Thamar University, Yemen
Beyond research
Teaching, service, and continuous development.
Teaching
Wireless Network SecurityInstructor · Spring · 2023-2024
Computer Networks and CybersecurityTeaching assistant and course support · Earlier teaching
ABET and academic supportAcademic support · 2020-2022
Academic contribution
Peer reviewReviewer for journals and conferences in networking, security, and machine learning.
PatentsSix granted US patents related to intelligent networks and connected systems.
Research collaborationSmart cities, IoT, smart grids, 5G/6G, federated learning, and edge intelligence.
Development
Deep Learning SpecializationNeural networks, optimization, and applied machine learning
Network and security trainingAdvanced wireless networks, cybersecurity, and research methods
Collaborate
Build networks that can think and defend.
For research collaboration, teaching, or professional inquiries, start with a direct email.
abdullatif2009@gmail.com