Shuhong Dai
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.
news
Nov 27, 2024 | 🎉🎉🎉 I’m thrilled to announce the release of TexHelper, a Python library designed to optimize and beautify TeX code. TexHelper makes managing your \(\LaTeX\)-based projects easier and more elegant. The project is open-source and available on GitHub. Check it out! 🤩 |
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Jul 05, 2024 | A paper on vehicle-road cooperation was accepted by IEEE IoT Journal. |
Jun 14, 2024 | Participated in Microsoft AI Day Beijing. |
Jan 02, 2024 | A paper on energy-efficient computing was accepted by Computer Communications. |
Dec 28, 2023 | A paper on data compression was accepted by IEEE IoT Journal. |
latest posts
selected publications
- MARP: A Cooperative Multi-Agent DRL System for Connected Autonomous Vehicle PlatooningIEEE Internet of Things Journal, 2024
- Approximate Data Mapping in Refresh-Free DRAM for Energy-Efficient Computing in Modern Mobile SystemsComputer Communications, 2024
- Deep Reinforcement Learning for Efficient IoT Data Compression in Smart Railroad ManagementIEEE Internet of Things Journal, 2023