Leijie (Eric) Wu

Leijie (Eric) Wu

I am too full of life to be half loved

About Me

Welcome to my personal space of interest!

I’m Leijie (Eric) Wu, currently a research scientist in the Theory Lab (Huawei 2012 Labs), Huawei Hong Kong Research Center (HKRC), joined at Dec. 2024.

I obtain my Ph.D. Degree from the Department of Computing (COMP) at the Hong Kong Polytechnic University (PolyU). My supervisor is Prof. Song Guo, who is currently a Chair Professor in the Department of Computer Science and Engineering (CSE) at the Hong Kong University of Science and Technology (HKUST).

Before joining PolyU in 2020, I received my Bachelor of Science in Automation at the Beijing Institute of Technology (BIT).

Since April 2023, I also join the Scalable Computing Systems Laboratory (SACS Lab) as a Visiting Ph.D. student, where I’m very fortunate to be supervised by Prof. Anne-Marie Kermarrec from the School of Computer and Communication Sciences (IC) at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.

My research is driven by a central question: how can we build AI systems that remain efficient, adaptive, and reliable under real-world constraints in data, computation, and knowledge? My earlier work focused on federated learning, federated unlearning, and edge intelligence, addressing data privacy, distributed collaboration, and resource constraints. Building on this foundation, my current research extends to foundation models and AI agents, with an emphasis on efficient inference and knowledge- and memory-augmented intelligence. My long-term goal is to develop efficient, knowledge-enhanced, and trustworthy AI systems that bridge advanced learning algorithms with scalable real-world deployment.

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