Zhonglin Sun

Zhonglin Sun is a Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His teaching responsibilities include the Artificial Intelligence undergraduate module, focusing on foundational AI concepts, intelligent agent design, and basic AI tools. His research spans advanced topics in computer vision and deep learning, including face recognition, synthetic data generation, emotion-aware frameworks, and underwater image restoration. Additionally, he explores applications of machine learning in power systems, such as intentional islanding and load-generation balance optimization.

Research interests include: Face Recognition (via deep learning, landmark-based methods, and semi-supervised learning), Computer Vision (synthetic face generation, spatial-temporal analysis), and Power Systems (self-embedding learning for grid stability). His work often intersects with neural network architectures like transformers and graph convolutional networks.

Recent publications emphasize robust solutions in face recognition under noise, data efficiency in deep learning, and energy system automation. No notable scientific awards are mentioned.

No grants or advising details are provided in the text. He collaborates within the School's facilities and research groups focused on electronic engineering and computer science.