Dr. LI Rongpeng

Networked Intelligence for sCience Exploring (NICE)

Author: Rongpeng Li

Dr. Li received the grant of “Program of Distinguished Young Scholars of Zhejiang Natural Science Foundation, China”.

On December 8, 2022, the Provincial Natural Science Foundation (i.e., Zhejiang Natural Science Foundation, China) announces this year’s granted programs. Among 74 granted programs for “Distinguished Young Scholars” this year, Dr. Li’s application (Task-oriented Mobile Networks for Decentralized Intelligence Service Provisioning) is proudly listed. This grant marks the latest acknowledgement of Dr Li’s works from
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He received the Wu Wenjun Artificial Intelligence Excellent Youth Award from China Association of Artificial Intelligence (CAAI).

China Association of Artificial Intelligence (CAAI) has just announced the results of 2021 Wu Wenjun Artificial Intelligence Science and Technology Award (吴文俊人工智能科学技术奖). Together with the other 14 scholars, Dr. Rongpeng Li has been awarded the Wu Wenjun Artificial Intelligence Excellent Youth Award, for its contribution to the integration of artificial intelligence and cellular networks (especially
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A project titled “Research on Full Service Awareness based Intelligence-Endogenous Networks” has been approved by National Science Foundation of China.

Project name in Chinese (项目中文题目：基于业务感知的内生智能通信网络研究) Abstract: Faced with the ever-growing services with increasingly diversified and scenario-based requirements, researchers from both academia and industry are resorting to a deeper integration of artificial intelligence (AI) and communications, so as to provide endogenous intelligence within cellular networks and further enhance the agility and flexibility of cellular networks. Unfortunately,
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A paper titled “GAN-powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing” with Dr. Li as Corresponding Author has been accepted by IEEE JSAC.

Paper abstract: Network slicing is a key technology in 5G communications system. Its purpose is to dynamically and efficiently allocate resources for diversified services with distinct requirements over a common underlying physical infrastructure. Therein, demand-aware resource allocation is of significant importance to network slicing. In this paper, we consider a scenario that contains several slices
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