Shuhong Dai

microsoft.png

Master's Student at

North China Electric Power University.

Research Assistant at

AI Lab, CRRC Academy.


daishuhong02@gmail.com

I am a master’s student in the School of Control and Computer Engineering at North China Electric Power University, pursuing my master’s degree in Computer Science. I received my bachelor’s degree in Electrical Engineering in 2023 and my research on fuzzy control was awarded the title of Excellent Graduation Thesis.

Prior to this, I was interested in embedded real-time operating systems and efficient switch-mode power supply control. I have won several competition awards, for example, the four-switch buck-boost circuit I designed won 1st Prize in the 2020 electronic design competition sponsored by Huawei. In 2022, the multi-vehicle system I developed earned the highest honor, the “TI Cup,” in the electronic design competition sponsored by Texas Instruments.

Currently, I am conducting research under the supervision of Prof. Long Cheng in the Distributed Systems Group he leads. My research focuses on the optimization of computing and decision-making in intelligent transportation systems. Additionally, I have also carried out some work in quantum computing.

Apart from academics, I enjoy strategy-based board games such as Go, Chinese Chess (Xiangqi), and chess. I also play strategy-oriented digital games, and have maintained a GrandMaster-level ranking (top 0.04%) in Teamfight Tactics for several seasons.

latest posts

selected publications

  1. QRL.png
    Quantum Reinforcement Learning for QoS-aware Real-time Job Scheduling in Cloud Systems
    Shuhong Dai, Nishant Saurabh, Qing-Le Wang, Jiawei Nian, Shuwen Kan, Ying Mao, and Long Cheng
    IEEE Systems Journal, 2025
  2. MARP.png
    MARP: A Cooperative Multi-Agent DRL System for Connected Autonomous Vehicle Platooning
    Shuhong Dai, Shike Li, Haichuan Tang, Xin Ning, Fang Fang, Yunxiao Fu, Qing-Le Wang, and Long Cheng
    IEEE Internet of Things Journal, 2024
  3. DataCompression.png
    Deep Reinforcement Learning for Efficient IoT Data Compression in Smart Railroad Management
    Xuan Chen, Qixuan Yu, Shuhong Dai, Pengfei Sun, Haichuan Tang, and Long Cheng
    IEEE Internet of Things Journal, 2023