Yiming Zhang is a PhD student in the Department of Computing at the Hong Kong Polytechnic University, under the supervision of Professor Hongxia Yang. His research focuses on the efficient deployment of Large Language Models (LLMs), with an emphasis on model merging and post-training quantisation. Yiming’s work aims to develop scalable and resource-efficient methods to integrate knowledge from multiple LLMs while reducing their computational and memory requirements. He holds a Master of Science degree from the Technical University of Munich (TUM), where he advanced his expertise in deep learning, and a Bachelor of Engineering from Harbin Institute of Technology. Yiming’s research combines his strong technical background with a practical focus on optimising LLM performance, contributing to advancements in the field of artificial intelligence and its real-world applications.