I am a fifth-year Ph.D. student with the Institute of Data Science and Engineering, School of Computer Science, Peking University, under the supervision of Dr. Wenfei Wu. My research focuses on distributed systems for AI, including LLM training, inference, and multi-agent systems. I graduated from the School of Electronics Engineering and Computer Science, Peking University, with a Bachelor's degree in Computer Science and Technology, and also from the National School of Development, Peking University, with a double Bachelor's degree in Economics.
News
Sep 2026AgentMesh accepted to ATC '26!
Aug 2026Presented Turbo at SIGCOMM 2026.
Jun 2026Homepage online.
Publications
(* Equal Contribution)
Multipath Collective Communication Beyond Scale-up Networks in GPU CloudsYuchen Xu, Jianglong Nie, Baojia Li, Mingzhuo Chen, Hao Lu, Guanyu Qu, Zhenchuan Liu, Shuangshuang Yin, Xiaojie Huang, Chunzhi He, Yinben Xia, Quan Wen, Xiang Li, Zekun He, Yachen Wang, Xianneng Zou, Congcong Miao, Wenfei Wu. 21st European Conference on Computer Systems (EUROSYS '26), 2026
MPCCS (EUROSYS '26): Multipath collective communication with scale-up and scale-out networks, accelerating AI training.
FlexComm (LANMAN '26): Flexible inter-collective scheduling without deadlocks, accelerating AI training.
LLM Inference & In-Network Computing
Turbo (SIGCOMM '26): In-network scaling-reduce on programmable switches to aggregate attention blocks, accelerating long-context AI inference.
Agentic Systems
AgentMesh (ATC '26): Identify and remove redundancies and barriers in agentic dataflow, accelerating multi-agent systems.
In-Network Computing
EPIC (SIGCOMM '26): Ethernet Polymorphic In-network Collective, for AI training and inference.
INARouting (TON '26): Routing for hierarchical in-network aggregation, for AI training.
PRISM (INCAS '25): Predictive scheduler for in-network aggregation, for AI training.
LHC (arXiv '24): Lossless Homomorphic Compression algorithm with in-network aggregation, for AI training.
Data Stream Mining / Network Measurement
MimoSketch (KDD '23 and TKDE '25): An unbiased data structure and algorithm framework for distributed frequency-based data stream mining tasks, including item frequency estimation.
Cuckoo Counter (TON '23): A cuckoo-hash-based data structure for frequency and top-k estimation in network measurement.