Federated Learning · Edge Intelligence · LLM Personalization
Ziming (Phoenix) Dai
Ph.D. Student, City University of Hong Kong
I work on personalized and deployable AI systems, with a focus on federated learning, edge intelligence, and large language model adaptation under privacy, latency, and resource constraints.
Current Focus
My current research explores how intelligent models can adapt to local contexts while remaining efficient, private, and practical for real-world edge and distributed environments.
Experience
360 Digital
NLP Engineer Intern, working on industrial language models and model enhancement.
Tianjin University
M.Eng. in Computer Technology at Edge Big Bang Lab, advised by Prof. Chao Qiu and Prof. Xiaofei Wang.
Beijing Wenge Technology
Algorithm Engineer Intern, focusing on named entity recognition for low-resource languages.
Tianjin University
B.Eng. in Artificial Intelligence.