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Pangpang Liu

Pangpang Liu

Quantitative Methods

Education

Ph.D. in Quantitative Methods, Purdue University, 2021 - present
M.S. in Statistics, Georgia State University, 2021
M.S. in Quantitative Economics, Fudan University, 2018
B.A. in Economics and B.A. in Law, China University of Political Science and Law, 2013

Pangpang Liu is a Ph.D. candidate in Quantitative Methods at the Daniels School of Business, with a concurrent M.S. in Industrial Engineering at the Edwardson School of Industrial Engineering, Purdue University, advised by Professor Will Wei Sun. His research interests focus on trustworthy AI, reinforcement learning, large language models, dynamic pricing, and empirical likelihood.

Starting in August 2025, he will work as a Postdoctoral Associate in the Department of Biostatistics at Yale University.

Journal Articles

  • Pangpang Liu, Zhuoran Yang, Zhaoran Wang, Will Wei Sun (2025). Contextual Dynamic Pricing with Strategic Buyers. Journal of the American Statistical Association, vol. 120 (550), 896–908. | Related Website |
  • Pangpang Liu, Yichuan Zhao (2024). Smoothed empirical likelihood for the difference of two quantiles with the paired sample. Statistical Papers, vol. 65 2077–2108. | Related Website |
  • Brian Pidgeon, Pangpang Liu, Yichuan Zhao (2024). Jackknife empirical likelihood for the correlation coefficient with multiplicative distortion measurement errors. Journal of Nonparametric Statistics, | Related Website |
  • Pangpang Liu, Yichuan Zhao (2023). A review of recent advances in empirical likelihood. WIREs Computational Statistics, vol. 15 (3), e1599. | Related Website |
  • Pangpang Liu (2017). An empirical analysis on the influence of option market on the volatility of spot market: Based on the comparison of before and after 50ETF option listing. Statistics & Information Forum, vol. 32 (10), 50-58. | Related Website |

Conference Proceedings

  • Pangpang Liu, Yichuan Zhao (2024). Empirical Likelihood for Fair Classification. The Twelfth International Conference on Learning Representations (ICLR), | Related Website |
  • Pangpang Liu, Fusheng Wang, George Teodoro, Jun Kong (2021). Histopathology image registration by integrated texture and spatial proximity based landmark selection and modification. IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1827-1830. | Related Website |

Working Papers

  • Pangpang Liu, Will Wei Sun (2025). Fairness-aware contextual dynamic pricing with strategic buyers. arXiv: 2501.15338. Major revision in Journal of the American Statistical Association, | Related Website |
  • Pangpang Liu, Will Wei Sun (2025). Inference of reinforcement learning from human feedback for uncertainty quantification in LLM training. In progress.
  • Pangpang Liu, Chengchun Shi, Will Wei Sun (2024). Dual active learning for reinforcement learning from human feedback. arXiv: 2410.02504. Under review, | Related Website |

Best Student Poster Award for the ASA Georgia Chapter, 2025

Doctoral Research Excellence Award, Purdue University, 2023

Doctoral Research Funds, Purdue University, 2024

First Prize in the Beijing Division of China Undergraduate Mathematical Modeling Competition, 2010

Fred Massey Scholarship, Georgia State University, 2021

Honorable Mention Poster, Statistics and Optimization in Data Science Workshop, 2023

Honorable Mention in the ASA SLDS Student Paper Competition, 2025

NSF Travel Award for ICSA, 2025

Outstanding Teaching Award, Purdue University, 2025

Ross Fellowship, Purdue University, 2021

Special Employee Performance Recognition Award, Purdue University, 2024

Travel Award, the Workshop on Biostatistics and Bioinformatics, 2023, 2025

Travel Grant, Purdue Graduate Student Government, 2024

Referee for Conferences

The International Conference on Learning Representations (ICLR)

Referee for Journals

Journal of the American Statistical Association, Computational Statistics and Data Analysis, Metrika, Journal of Applied Statistics, Statistical Analysis and Data Mining, Mathematical Methods of Statistics

  • MGMT 30500 (Business Statistics, Fall 2021, Spring 2022)
  • MGMT 57100 (Data Mining, Fall 2022, Fall 2024, Spring 2025)
  • MGMT 67000 (Business Analytics, Fall 2024)

Contact

liu3364@purdue.edu
Phone: (765) 494-4524
Office: KRAN 486

Quick links

Google Scholar
LinkedIn

Area(s) of Expertise

Artificial Intelligence, Machine Learning, Optimization, Pricing, Quantitative Analysis