The Chinese University of Hong Kong, Shenzhen
We focus on the intersection of Next-Gen Networking, AI for Science, and Distributed Systems.
The Network and Artificial Intelligence System (NAIS) Lab is based on the School of Science and Engineering (SSE) and the Future Network of Intelligence Institute (FNii) at The Chinese University of Hong Kong, Shenzhen (CUHK-SZ), led by Dr. Fangxin Wang.
Our mission is to build intelligent systems that bridge the physical and digital worlds. We aim to identify and solve critical challenges in Next-Generation Networking, AI for Science, and Distributed Systems, developing scalable and efficient infrastructure for the intelligent era.
Advancing the foundational and general capabilities of AI models, such as large language models (LLMs), multimodal large models, and world models, while achieving lightweight, high-efficiency and privacy-preserving deployment.
Investigating how AI models/agents, particularly with distributed collaboration, can empower communication network and address practical challenges, including video streaming, task scheduling, network operations, semantic communications, and so on.
Exploring high-precision and lightweight perception, understanding, reconstruction, and computation of spatial features of the world, advancing physical AI, and further enabling embodied decision-making and control.
We are actively looking for self-motivated Postdocs, PhDs, MPhils, and RAs to join our team.
Our ongoing research, system demonstrations, and open-source datasets.
High-fidelity digital twin of the CUHK-Shenzhen campus, reconstructed using 3D Gaussian Splatting from extensive scanner and drone aerial data.
A Synchronized Dataset Bridging Fine-grained Motion Tracking and High-Fidelity Multi-View Video.
A Large-Scale Dataset of Head and Gaze Behavior for 360-Degree Videos, please refer to our paper published in ACM MM 2022.
A Dataset of Full Scene Volumetric Video, please refer to our paper published in ACM MMsys 2023.
Research Interests: AI for Networking and System, Large Models, Multimedia Networking
BS from SUSTech
MS from HK CityU
BS from CSU
MS from BJTU
MS from UESTC
MS/BS from CUHKSZ
BS from SCU
BS from BJTU
BS from CUHKSZ
BS from BIT
BS from SWJTU
BS from TYUT
CUHK-Shenzhen
PhD 2025 → Asst. Prof @ CNU
MPhil 2025 → Versee Tech
MPhil 2025 → PhD @ SFU
MPhil 2025 → PhD @ PKU
MPhil 2024 → PhD @ THU
MPhil 2024 → PhD @ McGill
MPhil 2023 → PhD @ ZJU&SFU
MPhil 2023 → PhD @ McGill
MPhil 2023 → PhD @ PolyU&NJU
MPhil 2023 → Intel
MPhil 2023 → Bilibili
BS 2025 → MS @ UIUC
BS 2025 → MS @ UCSD
BS 2024 → PhD @ USC
BS 2022 → PhD @ UofT
