网络智能研究中心（NIRC）隶属于北京邮电大学“网络与交换技术国家重点实验室”，研究领域从移动智能网、业务网络发展到网络智能基础理论和应用技术，体现了理论研究、技术开发和工程应用紧密结合的鲜明特色。

实验室研究方向涵盖人工智能与网络的多个方面，如智慧云网络、大数据分析、机器视觉、自然语言处理与人机交互等。

NIRC回归科学技术本源，坚持系统级创新，希望对本领域技术进步有所推动，也欢迎同行们的关注和引用。

The Network Intelligence Research Center (NIRC) is part of the State Key Laboratory of Networking and Switching Technology at Beijing University of Posts and Telecommunications. NIRC's research portfolio spans from mobile intelligent networks and service networks to the fundamental theories and applications of network intelligence.

NIRC's current research directions involve multiple aspects of artificial intelligence and networking, such as intelligent cloud networks, big data analysis, computer vision, natural language processing, and human-computer interaction.

The NIRC is committed to pushing forward technical advancement in network intelligence and related fields. We welcome colleges and communications from both academia and industry.

DSMRC-S is an extractive summarization method based on machine reading comprehension and distant supervision, and it has been published as "Distant Supervision based Machine Reading Comprehension for Extractive Summarization in Customer Service", SIGIR 2021. [Paper] [Code]

GRSGD is a gradient sparsification method to accelerate the distributed edge learning process, and it has been published as "Following the Correct Direction: Renovating Sparsified SGD Towards Global Optimization in Distributed Edge Learning" in IEEE Journal on Selected Areas in Communications, 2022. [Paper] [Code]

GSSP groups edge nodes with similar performance together to eliminate tragglers in the heterogeneous edge environment and refine the model weights, and it has been published as "GSSP: Eliminating Stragglers Through Grouping Synchronous for Distributed Deep Learning in Heterogeneous Cluster" in IEEE Transactions on Cloud Computing, 2022. [Paper] [Code]