Alim Ul Gias

Dr. Alim Ul Gias is a Lecturer in Programming at Queen Mary University of London, with a PhD in Computing from Imperial College London. He has over a decade of academic experience across institutions in the UK and Bangladesh, including roles at City, University of London and the University of Dhaka. His research focuses on software engineering, distributed systems, and performance optimization in cloud/edge computing, employing reinforcement learning and predictive analytics. He also investigates AI-assisted education tools to bridge theory-practice gaps in computing education.

Education: PhD (Imperial College London), M.Sc. (Software Engineering, University of Dhaka), B.Sc. (Information Technology, University of Dhaka). Completed an internship at Grameenphone during his undergraduate studies.

Research Interests: Intelligent performance management, cloud-native applications (microservices), DevOps challenges, and AI-driven educational resources. His work emphasizes open-source tools for net-zero computing and smart manufacturing. Recent publications explore trace sampling (SampleHST-X), cold-start capacity planning (COCOA), and model-driven autoscaling (ATOM).

Teaching: Courses include Software Engineering Tools, Algorithms and Data Structures, and Quality Assurance in Software Industry.

Labs/Teams: Active contributor to the RADON framework for microservices performance engineering. Collaborates on open-source projects addressing distributed system reliability and scalability.