Tianyu Gu

Doctoral Student

McClelland Hall 320C
 

Areas of Expertise

  • Econmetics
  • Deep learning and statistical learning
  • Natural language processing
  • Digital marketing
  • Online reviews
  • Crowdfunding and other internet-enabled platforms

Additional Links

Bio

Gu joined the doctoral program in 2014. Prior to that, he served as a research assistant in the Visual Analytic Group, State Key Lab of CAD&CG during his undergraduate period. Gu received a B.S. in Information and Computing Science from Zhejiang University. His research interest includes econometrics, deep Learning and statistical learning, natural language processing, digital Marketing, online reviews, crowdfunding and other internet-enabled platforms. Gu's previous research in data visualization has been presented at several international academic conferences.

Research

Working Papers:
Tianyu Gu, Yong Liu, Madhu Viswanathan, “Differentiation in Online Product Reviews: A Machine Learning Based Analysis”, job market paper, under review at Marketing Science
Tianyu Gu, Bikram Ghosh, Yong Liu, “Effects of Text and Image on Reward-Based Crowdfunding Performance”, being finalized for submission to Journal of Marketing Research
Tianyu Gu, Yong Liu, Junming Yin, “Capturing Virtual Business Opportunities from Real-World Events”, manuscript being prepared for submission to Management Science
Nooshin L. Warren, Matthew Farmer, Tianyu Gu, Caleb Warren, “How to Write Research Papers That Have a Larger Impact”, being finalized for submission to Journal of Consumer Research

Peer-Reviewed Publications:
Wang, Fei, Wei Chen, Ye Zhao, Tianyu Gu, Siyuan Gao, and Hujun Bao. “Adaptively exploring population mobility patterns in flow visualization.” IEEE Transactions on Intelligent Transportation Systems 18, no. 8 (2017): 2250-2259.
Wang, Fei, Wei Chen, Feiran Wu, Ye Zhao, Han Hong, Tianyu Gu, Long Wang, Ronghua Liang, and Hujun Bao. “A visual reasoning approach for data-driven transport assessment on urban roads.” In 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 103-112. IEEE, 2014.

Conference Presentations:
"Understanding Review Differentiation and Its Motivations: A Machine Learning Based Text Analysis of Yelp Reviews"

  • China Marketing International Conference, Shanghai, 2018
  • INFORMS Marketing Science Conference, Los Angeles, CA, 2017

"Capturing Virtual Business Opportunities from Real-World Events: Findings and Insights from Sports Video Games"

  • Wharton Customer Analytics Initiative Symposium, San Francisco, CA, 2017

"A Visual Reasoning Approach for Data-Driven Transport Assessment on Urban Roads"

  • China Visualization Conference, Beijing, 2014