Zhenan Fan (范喆楠)

I am currently a Staff Research Engineer at the Huawei Vancouver Research Center, where I work on optimizing large language model (LLM) inference and deployment within the Huawei AI CloudMatrix platform(华为云超节点). My recent research focuses on efficient LLM serving, with particular emphasis on multi-LoRA inference, disaggregated serving architectures, and SLO-aware scheduling algorithms for large-scale cloud environments.

Prior to my work on LLMs, I was actively involved in the design and development of OptVerse(天筹求解器), Huawei’s in-house large-scale optimization solver. My contributions centered on algorithmic innovations and system-level integration to support real-world optimization tasks in cloud-based applications.

I obtained my Ph.D. in Computer Science from The University of British Columbia, under the supervision of Prof. Michael P. Friedlander. My doctoral research addressed large-scale structured optimization problems, with applications in machine learning, data mining, and signal processing.

Education

PhD, University of British Columbia, Computer Science (2022)

MS, University of British Columbia, Computer Science (2019)

BSc, University of Toronto, Mathematics (2017)