Sukhpal Singh Gillمشاهده پروفایل
استادیار
- Cloud Computing
- Fog Computing
- Edge AI
- +۷ مورد دیگر
Sukhpal Singh Gill is an Assistant Professor (Lecturer) in Cloud Computing at the School of Electronic Engineering and Computer Science, Queen Mary University of London (UK). He holds a PhD, ME, and BE in Computer Science and is a Fellow of the Higher Education Academy (FHEA). His roles include Programme Director for MSc Advanced Computer Science and MSc Business Analytics, as well as Deputy Chair of the Main Misconduct Panel. He leads the GillNet Research Lab and is the Editor-in-Chief of the International Journal of Applied Evolutionary Computation (IJAEC) , with editorial roles in IEEE IoT, Nature Scientific Reports, and other journals. Education: PhD in Computer Science ME in Computer Science BE in Engineering Research Interests: Focus on Cloud Computing, Edge AI, IoT, Energy Efficiency, and Quantum Computing. His work bridges theoretical advancements with practical applications in healthcare, smart cities, and sustainable computing. Notable projects include AI-driven frameworks for carbon-neutral cloud resource management, blockchain-empowered healthcare systems, and quantum cloud computing models. Teaching: Teaches modules such as Cloud Computing (Postgraduate), Fundamentals of Web Technology (Undergraduate), and Semi-structured Data and Advanced Data Modelling (Postgraduate/Undergraduate). He emphasizes inclusive curriculum design and innovative teaching tools like the Q-Module-Bot for AI-supported learning. Awards & Grants: Recipient of 12,500+ citations and an H-index of 54 (Google Scholar). Secured grants for projects on edge AI, federated learning, and sustainable cloud computing. Winner of awards including the IEEE IT Professional Magazine Outstanding Reviewer Award (2024) and Elsevier's Best Paper Award (2023). Labs & Teams: Leads the GillNet Research Lab , focusing on cutting-edge research in cloud-edge computing, AI, and quantum systems. Collaborates with industry partners on projects like HealthEdgeAI and AIoT-driven smart healthcare systems .











