Mr.Pang Zirui is a current student at the University of Illinois Urbana-Champaign, pursuing a Master’s degree in Predictive Analytics and Risk Management in the College of Liberal Arts & Sciences, Department of Mathematics. He is also a member of the iRisk Lab at the same university. He completed his undergraduate studies at Central University of Finance and Economics, where he majored in Data Science and Big Data Technology in the School of Statistics and Mathematics. Through his past research projects and internship experiences, Pang Zirui has developed a strong interest in the application of machine learning algorithms, data science, and actuarial science in finance, as well as quantitative finance. He is actively seeking research projects and research assistant positions in these areas and is highly motivated to pursue a Ph.D. or research role in the future.

Education

• M.S. in Predictive Analytics and Risk Management, University of Illinois Urbana-Champaign (UIUC), 2024-present

• B.S. in Data Science and Big Data Technology, Central University of Finance and Economics (CUFE), 2019-2023

Work Experience

• 2023.2-2023.4 : Assistant Software Development Engineer
  • Odeon Big Data Platform R&D Department, AI Engineering Institute, iFLYTEK

Research Experience

• 2024.12-present: Research Assistant
  • The Hong Kong University of Science and Technology (Guangzhou)
• 2024.8-2024.12: Assistant Researcher
  • Luyan Project, IRisk Lab, University of Illinois Urbana-Champaign
• 2024.8-2024.10: Research Assistant
  • University of Illinois Urbana-Champaign (College of Liberal Arts & Sciences)
  • Data Processing Project: By comparing the performance of models after processing data with different data preprocessing methods, we validated the impact of preprocessing on model effectiveness
  • superviser: Assistant Professor Frank Quan
• 2024.7-2024.8 : Research Assistant
  • Central University of Finance and Economics (School of Statistics and Mathematics)
  • NQI Project: Assisted the team in completing the data mining portion of the NQI project. Utilized OCR technology and regular expressions to convert PDF files into structured data for research purposes.
  • superviser: Assistant Professor Yushan Xue
• 2021.7-2021.11: Research Assistant
  • Central University of Finance and Economics (School of Statistics and Mathematics)
  • Designed Python-based web crawler program, scraping government bidding documents ranging from 1991 to 2021 from www.ccgp.gov.cn (500g in all)
  • Cleaned and organized data achieved, forming a dataset with 170 dimensions to meet the requirements
  • superviser: Professor Fuguo Cao