CV

Education

• MEng in Electronic Information, University of Science and Technology of China, 2023-Now
• BSc in Data Science, University of Science and Technology of China, 2019-2023

Work experience

• 2023.3-Now: Intern at Kuaishou
  • Responsibilities:
    • Conducted scientific research on recommendation algorithms.
    • Developed and optimized online algorithms to enhance user engagement.
  • Supervisor: Qingpeng Cai
  • Key Achievements:
    • Improved average app time by +0.120%.
    • Enhanced metrics on the curated page:
      • Follow rate: +1.002%
      • Forward rate: +0.984%
      • Download rate: +1.018%
      • Collection rate: +1.102%
      • Reduced negative feedback: -2.627%
    • Published one paper in WSDM’25

Skills

• Programming Skills
  • Proficient in:
    • PyTorch: Deep learning framework for research and development.
    • TensorFlow: Specialized in recommendation system implementations.
    • LLM Fine-Tuning: Experience in fine-tuning large language models.
• Language Proficiency
  • English: TOEFL Score: 98

Publications

DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems

Chen, J., Gao, C., Yuan, S., Liu, S., Cai, Q., & Jiang, P. (2024). DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems. arXiv preprint arXiv:2408.12470.

Treatment Effect Estimation for User Interest Exploration on Recommender Systems

Chen, J., Wenjie, W., Gao, C., Wu, P., Wei, J., & Hua, Q. (2024, July). Treatment Effect Estimation for User Interest Exploration on Recommender Systems. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1861-1871).