My research focuses on Autonomic Computing and its application to large-scale distributed systems, including Clouds, Smart Grids, Wireless Sensor Networks, and pervasive and mobile computing systems. I am particularly interested in learning at scale systems used for Massive Open Online Courses (MOOCs), addressing both technological bottlenecks and conceptual challenges in complex system management.Additionally, I explore the role of AI and multi-agent systems to enhance the adaptability and resilience of distributed systems. My work includes designing protocols that enable efficient operation and decision-making among autonomous agents.Research Areas:- Autonomic Computing and Multi-Agent Systems (AI-Agent included): I investigate the coordination of multiple autonomic control loops and develop AI-driven multi-agent protocols to ensure system stability and consistency. This includes creating systems capable of self-configuration, self-healing, self-protection, and self-optimization. I leverage AI to improve the decision-making capabilities of autonomous agents, enabling more robust and adaptive distributed systems.- AI in Learning at Scale Systems: I leverage AI to develop systems and tools for MOOCs that dynamically scale to support large student populations. This includes implementing AI-driven techniques for personalized learning analytics and assessments, enhancing the scalability and effectiveness of online learning platforms.- Cloud Computing and Data Center Efficiency: Researching SaaS, PaaS, and IaaS, with a focus on virtual machine consolidation to enhance data center efficiency.- High-Performance and Grid Computing: Utilizing General-Purpose computing on Graphics Processing Units (GPGPU) and grid computing to improve computational performance.- Green Computing and Smart Systems: Exploring energy-efficient solutions for smart grids, wireless sensor networks (WSN), and promoting sustainable computing practices.