CV

Education

• Ph.D in Engineering, University of Toyama (expected)
• M.S. in Management, Graduate School of Chinese Academy of Agricultural Sciences, 2022 - 2025
• B.S. in Management, Harbin University of Science and Technology, 2018 - 2022

Research experience

• Information Mining for Germplasm Resources Applications in Staple Crops
  • 2024.01 - 2024.12
  • Advisor: Jingchao Fan
  • Research Direction: Efficient information mining based on Large Language Models
  • Research Content: Utilizing large language models to mine crop germplasm resource information from data types such as books, research paper abstracts, and full-text PDFs of research papers, thereby accelerating breeding, and further proposing recommendations for using large language models to complete downstream tasks.
• Application Demonstration for Convergent Science Scenarios
  • 2021.12 - 2024.11
  • Advisor: Jingchao Fan
  • Research Direction: Categorized Study of Agricultural Science and Technology Policies in the Yellow River Basin
  • Research content: Collect data on agricultural science and technology policies in the nine provinces along the Yellow River. Based on this data, define quantitative standards and calculation formulas for policies, and conduct a quantitative analysis of agricultural science and technology policies in the nine provinces along the Yellow River.Based on the analysis results, define classification indicators for agricultural science and technology policies. Use deep learning methods to construct a classification model for agricultural science and technology policies, and use large language model technology to construct a policy classification tool that combines the security of deep learning models with the efficiency of large language models.

Work experience

• 2025.03 - 2025.06: Prompt Engineer (Internship)
  • Beijing Huizhixintong Co., Ltd.
  • Duties includes:
    • (1) Research and develop prompt strategies for AI models to ensure that generated content meets expected quality standards and style requirements.
    • (2) Gain a deep understanding of business needs and translate abstract concepts into concrete, effective prompts to drive AI to generate high-quality content in specific domains.
    • (3) Collaborate with cross-functional teams, including R&D, product managers, and operations, to jointly define and optimize prompt engineering processes.
    • (4) Analyze the quality of AI-generated content, identify and address potential bias issues, and continuously improve prompt design and effectiveness.
    • (5) Stay updated on the latest NLP research and technological advancements, explore innovative prompting methods, and enhance the diversity and accuracy of AI-generated content.
• 2019.01 - 2019.04: Front-end Developer (Internship)
  • Hangzhou Red Dot New Technology Co., Ltd.
  • Duties included: Design and develop front-end web pages and implement front-end and back-end interactions.

Publications

Chat-rgie: precision extraction of rice germplasm data using large language models and prompt engineering

Wei Yijin, Fan Jingchao. (2025). Chat-rgie: precision extraction of rice germplasm data using large language models and prompt engineering. Journal of Big Data, 12(1): 202.

Information Extraction from Chinese Wheat Varieties Journal Based on Large Language Model

Wei Yijin, Chen Yanqing, Wang Xiudong & Fan Jingchao. (2025). Information Extraction from Records of Chinese Wheat Varieties Based on Large Language Models. Frontiers of Data and Computational Development (Chinese and English), 7(01), 175−185.

Classification Model of Agricultural Science and Technology Policies Based on Improved BERT-BiGRU-Attention

Wei Yijin & Fan Jingchao. (2024). An Agricultural Science and Technology Policy Classification Model Based on Improved BERT-BiGRU-Attention. Frontiers of Data and Computational Development (Chinese and English), 6(06), 53−61.

Construction of A Knowledge Graph for Selection and Breeding Research of New Potato Varieties in China Based on GraphRAG

Wei Yijin, Ren Youqiang, Zhao Hui, Fan Jingchao, Fang Wei & Yan Shen. (2025). Construction of a Knowledge Graph for New Potato Varieties in China Based on GraphRAG. Journal of Plant Genetic Resources, 26(06), 1229−1241. doi:10.13430/j.cnki.jpgr.20240919001.

An Agricultural Policy Question Answering System Based on ChatGLM2-6B

Wei Yijin & Fan Jingchao. (2024). Agricultural Policy Q&A System Based on ChatGLM2-6B. Frontiers of Data and Computational Development (Chinese and English), 6(04), 116-127.

Ploidy Analysis Set of National Indigenous Varieties of Deciduous Fruit Trees Resources in 2012-2017

Wei Yijin, Wang Xiaoli, Li Haoxian, Hu Lin, Fan Jingchao & Cao Shangyin. (2023). Ploidy Analysis Dataset of Indigenous Varieties of Deciduous Fruit Trees in Dominant Production Areas during 2012−2017. Journal of Agricultural Big Data, 5(01), 34−39. doi:10.19788/j.issn.2096-6369.230111.

Achievements

• 2023-2024 Second Class Academic Scholarships for the Graduate School of the Chinese Academy of Agricultural Sciences, September 2024
• Excellent in mid-term assessment, July 2024
• Third Prize of the 11th “Sharing Cup” Science and Technology Resources Sharing Service Innovation Competition (Agricultural Science Specialized Competition), April 2024
• Winner Award of National Artificial Intelligence Application Scenario Innovation Challenge, December 2023
• 2022-2023 First Class Academic Scholarships for the Graduate School of the Chinese Academy of Agricultural Sciences, September 2023
• First prize of the 10th “Sharing Cup” Science and Technology Resources Sharing Service Innovation Competition, April 2023
• Grand Prize of the 10th “Sharing Cup” Science and Technology Resources Sharing Service Innovation Competition (Agricultural Science Specialized Competition), April 2023

Skills

• Programming Languages
  • Python
  • HTML/CSS
  • JavaScript
• Language
  • Chinese
  • English
  • Japanese (N1)