Steve Uhlig

Professor Steve Uhlig holds the position of Professor of Networks and Head of School at Queen Mary University of London's School of Electronic Engineering and Computer Science. His expertise spans AI-driven networking, cloud computing sustainability, and interdisciplinary applications in healthcare and education technology.

Research interests include advancing edge and fog computing frameworks, generative AI in resource management, quantum computing challenges, and leveraging machine learning for sustainable systems. He explores topics like serverless computing optimization, explainable AI (XAI), and blockchain-enhanced IoT healthcare solutions. His work also addresses educational impacts of AI, such as curriculum redesign and online learning environments.

In publications, he emphasizes proactive orchestration in Kubernetes, energy-efficient cloud resource allocation, and cold-start latency mitigation in serverless systems. Notable contributions include frameworks like COUNTER, ProKube, and PRICELESS, which integrate AI for network and computational efficiency. His research highlights trends in sustainable computing, AI deployment at network edges, and quantum computing's future directions.

No scientific awards or grants are explicitly mentioned in the provided texts. He advises no listed students but teaches postgraduate modules such as Applied Statistics, focusing on practical data analysis and probabilistic modeling.