Jiajie Yin（尹家杰）

Jiajie Yin（尹家杰）

The picture shows a little stray cat living near my dormitory. Its name is Guogai (锅盖).

About Me

Jiajie Yin is an undergraduate student at Beijing Normal University majoring in Data Science and Big Data Technology. With a strong foundation in mathematics, programming, and data analysis, he has excelled academically. Jiajie has participated in several research projects, including developing interactive simulation platforms for swarm behavior and optimizing resource allocation in mobile edge computing with UAV systems. Supervised by Prof. Zhiqing Tang, their research has led to published work in top-tier journals (IEEE IoT-Journal, JCR-Q1) and a national patent. Recently, Jiajie has been recommended for admission and accepted into Huazhong University of Science and Technology to pursue a master’s degree in Computer Science and Technology.

My research interests include multi-agent systems, decision intelligence, deep reinforcement learning, and edge computing, with a focus on applying AI to swarm intelligence and IoT.

I am looking for opportunities to collaborate on research projects. Please contact me if you are interested in my profile!

Education and Experience

  • Zhengzhou Foreign Language School （Sep 2018 - Jun 2021）
  • Beijing Normal University (BNU) (Sep 2021 - Present)
    • B.Sc. in Data Science and Big Data Technology
    • Relevant Coursework: Mathematics Analysis, Probability and Statistics, Database Systems, Deep Learning, Data Mining
  • Huazhong University of Science and Technology (HUST) (Expected to start since Sep 2025)
    • M.Sc. in Computer Science and Technology, supervised by Prof. Yixue Hao
    • Expected Research Focus: Multi-agent Systems and Reinforcement Learning
  • RA in Institute of AI and Future Networks , Beijing Normal University (Sep 2023 – Present)
    • Conducted research on deep reinforcement learning and its applications in areas such as edge computing and agents, under the guidance of Prof. Zhiqing Tang, Prof. JianXiong Guo and Prof. Weijia Jia.

Skills

  • Programming Languages: Proficient in Python for algorithm design, data analysis, and simulation modeling. Experienced in Java for object-oriented programming, database interfacing, and network programming. Knowledgeable in C/C++ for algorithms and data structures.
  • Deep Learning Frameworks: Extensive experience with PyTorch; familiar with reading and reproducing code in TensorFlow.
  • Software Tools: Competent with Matlab and R; experience using STATA and SPSS for data analysis.

Publicacion

  1. QoS-aware Energy-efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile Edge Computing
    Jiajie Yin, Zhiqing Tang*, Jiong Lou, Jianxiong Guo, Hui Cai, Xiaoming Wu, Tian Wang, Weijia Jia
    IEEE Internet of Things Journal (IoT-J), 2024, Early Access. (JCR-Q1) [DOI] [PDF]
  2. Data-Driven MMA Outcome Prediction Enhanced by Fighter Styles: A Machine Learning Approach
    Jiajie Yin*
    2024 4th International Conference on Machine Learning and Intelligent Systems Engineering (MLISE). IEEE, 2024: 346-351. (EI) [DOI] [PDF]

Projects

  • The Study on Mechanisms and Patterns of Two Opposing Swarm Movements (Physics/Complex Systems, 2022–2023)
    (National Class Project) (Undergraduate Training Programs for Innovation and Entrepreneurship)

    This research project was supervised by Dr. Guiyuan Shi from the International Academic Center of Complex Systems, Advanced Institute of Natural Sciences, Beijing Normal University.
    As a core member, I led the key aspects of the project, including:

    • Implemented classical swarm models like Boids, Vicsek, and Couzin using Python.
    • Extended models to 3D space and introduced opposing swarms, designing interaction mechanisms to study their dynamic behaviors.
    • Developed an interactive simulation platform, CouzinSim, featuring customizable parameters and clear visualizations. The tool serves both research and educational purposes and is available on GitHub.

  • Online Container Scheduling and Resource Optimization for Digital Twin Edge Networks (Participate as an undergraduate RA, 2023–Present)
    (National Class Project) (Supported by the Young Scientists Fund of the National Natural Science Foundation of China)

    This research project was supervised by Prof. Zhiqing Tang.
    We introduced a composite user model to enhance system reliability by addressing the challenges of high mobility and heterogeneity in edge computing scenarios. A novel reinforcement learning approach is proposed for optimizing UAV task scheduling and resource allocation. We conducted extensive simulations to validate the proposed algorithm’s superior performance in large-scale UAV-MEC scenarios. As the first author, I contributed to a paper and a patent application:

    • Publication: QoS-aware Energy-efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile Edge Computing (IEEE IoT-Journal, JCR-Q1) [PDF]
    • Patent: Method and Device for UAV-Assisted Offloading Strategy (Patent Application No. 2024109978530)

Honors

  • Second Prize of “Jingshi” Undergraduate Scholarship, Beijing Normal University
  • Honourable Mention, the Mathematical Contest in Modeling (MCM)
  • Second Prize (Guangdong Division), the 15th Lanqiao Cup (Python)
  • First Prize (Ranked #1), Beijing Normal University “Jingshi Cup” Science and Technology Competition
  • Outstanding Officer of 2021 - 2022, Beijing Normal University Zhuhai Education Development Foundation of Guangdong Province