Pengyuan headshot

Pengyuan Wang

  • Associate Professor, Department of Marketing

Education

  • PhD, Statistics, Wharton, U. of Pennsylvania, 2012

Research Interests

  • Online advertising
  • Digital marketing
  • Related stat/ML/AI techniques

Publications

Journal Articles

  • Pengyuan Wang, Li Jiang, and Jian Yang (2023), “Internet search data showed increased interest in supplementary online education during the COVID-19 pandemic, with females showing a greater increase,” Frontiers in Education, Volume 8.
  • Pengyuan Wang, Li Jiang, and Jian Yang (2023), “The Early Impact of Requesting GDPR Explicit Consent on Display Advertising: The Case of an Ad Publisher,” Journal of Marketing Research, forthcoming.
  • Smith, Rosanna K., Elham Yazdani, Pengyuan Wang, Saber Soleymani, and Lan Anh N. Ton (2022), “The Cost of Looking Natural: Why the No-Makeup Movement May Fail to Discourage Cosmetic Use,” Journal of the Academy of Marketing Science, Volume 50, pp. 324–337.
  • Pengyuan Wang, Anindita Chakravarty, and Jian Yang (2021), “Can Emotions be Used as Keywords for Text-based Search Engine Advertising?,” Journal of Interactive Advertising, Volume 21, pp. 159-172.
  • Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang, Jian Yang, and Will Wei Sun (2021), “Sparse Tensor Additive Regression,” Journal of Machine Learning Research, Volume 22, pp. 1−43.
  • Pengyuan Wang, Guiyang Xiong, and Jian Yang (2019), “Frontiers: Asymmetric Effects of Recreational Cannabis Legalization,” Marketing Science, Volume 38, Issue 6, pp. 913-1084.
  • Pengyuan Wang, Guiyang Xiong, and Jian Yang (2018), “Serial-Position Effects on Native-Advertising Effectiveness: Differential Results across Publisher and Advertiser Metrics,” Journal of Marketing, Volume 83, Issue 2, pp. 82-97.
  • Yue Wang, Dawei Yin, Jie Luo, Pengyuan Wang, Makoto Yamada, Yi Chang, Qiaozhu Mei (2018), “Optimizing Whole-Page Presentation for Web Search,” ACM Transactions on the Web (TWEB), Volume 12, Issue 3, pp. 1-25.
  • Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-Chih Lee, Zenglin Xu, Alan Qi, and Zoubin Ghahramani (2016), “Distributed Flexible Nonlinear Tensor Factorization,” Proceedings of the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS).
  • Yue Wang, Dawei Yin, Jie Luo, Pengyuan Wang, Makoto Yamada, Yi Chang, and Qiaozhu Mei (2016), “Beyond Ranking: Optimizing Whole-Page Presentation,” Proceedings of the 9th ACM International Conference on Web Search and Data Mining (WSDM), pp. 103-112. Best Paper Award.
  • Pengyuan Wang, Dawei Yin, Marsha Meytlis, Jian Yang, and Yi Chang (2015), “Rethink Targeting: Detect ‘Smart Cheating’ in Online Advertising through Causal Inference,” Proceedings of the 8th World Wide Web Conference (WWW), pp. 133-134.
  • Pengyuan Wang, Wei Sun, and Dawei Yin (2015), “What Size Should A Mobile Ad Be?” Proceedings of the 8th World Wide Web Conference (WWW), pp. 943-944.
  • Wei Sun, Pengyuan Wang, Dawei Yin, Jian Yang, and Yi Chang (2015), “Causal Inference via Sparse Additive Models with Application to Online Advertising,” Proceedings of the 29th AAAI Conference on Artificial Intelligence, pp. 297-303.
  • Pengyuan Wang, Wei Sun, Dawei Yin, Jian Yang, and Yi Chang (2015), “Robust Tree-based Causal Inference for Complex Ad Effectiveness Analysis,” Proceedings of the 8th ACM International Conference on Web Search and Data Mining (WSDM), pp. 67-76.
  • Pengyuan Wang, Yechao Liu, Marsha Meytlis, Han-Yun Tsao, Jimmy Yang, and Pei Huang (2014), “An Efficient Framework for Online Advertising Effectiveness Measurement and Comparison,” Proceedings of the 7th ACM International Conference on Web Search and Data Mining (WSDM), pp.163-172.
  • Pengyuan Wang, Eric T. Bradlow, and Edward I. George (2014), “Meta-Analyses Using Information Reweighting: An Application to Online Advertising,” Quantitative Marketing And Economics, 12(2).
  • Elea McDonnell Feit, Pengyuan Wang, Eric Bradlow, and Peter Fader (2013), “Fusing Aggregate and Disaggregate Data with an Application to Multi-Platform Media Consumption,” Journal Of Marketing Research,50(3).
  • Pengyuan Wang, Mikhail Traskin, and Dylan Small (2013), “Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups,” Journal of Causal Inference, Volume 1, Issue 2, pp. 209 – 234.

Prior Professional Positions

  • Senior Research Scientist, Yahoo Labs, 2013 to 2016