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Daniel Yue

Daniel Yue

Doctoral Student

Doctoral Student

Daniel is a doctoral candidate in the Technology and Operations Management Unit at Harvard Business School. His research focuses on how firms leverage data analytic methodologies to create competitive advantage. In particular, he focuses on the use of two dominant statistical frameworks — experimentation and prediction (artificial intelligence) — and the organizational processes necessary to make them work. Before joining HBS, Daniel was a Product Manager at Mastercard (Applied Predictive Technologies), where he designed analytics software to guide businesses in conducting and analyzing field experiments on strategic initiatives. He graduated with an AB in Physics from Harvard College in 2016.
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Daniel Yue
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Publications

Working Papers
Working Papers

  • Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. View Details

Cases and Teaching Materials
Cases and Teaching Materials

  • Greenstein, Shane, Daniel Yue, Kerry Herman, and Sarah Gulick. "Hugging Face: Serving AI on a Platform." Harvard Business School Case 623-026, November 2022. (Revised January 2023.) View Details
All Publications
Daniel is a doctoral candidate in the Technology and Operations Management Unit at Harvard Business School. His research focuses on how firms leverage data analytic methodologies to create competitive advantage. In particular, he focuses on the use of two dominant statistical frameworks — experimentation and prediction (artificial intelligence) — and the organizational processes necessary to make them work. Before joining HBS, Daniel was a Product Manager at Mastercard (Applied Predictive Technologies), where he designed analytics software to guide businesses in conducting and analyzing field experiments on strategic initiatives. He graduated with an AB in Physics from Harvard College in 2016.
Working Papers
  • Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. View Details
Cases and Teaching Materials
  • Greenstein, Shane, Daniel Yue, Kerry Herman, and Sarah Gulick. "Hugging Face: Serving AI on a Platform." Harvard Business School Case 623-026, November 2022. (Revised January 2023.) View Details
Area of Study
  • Technology and Operations Management
Areas of Interest
  • analytics
  • decision-making
  • information technology
  • technological innovation

Area of Study

Technology and Operations Management

Areas of Interest

analytics
decision-making
information technology
technological innovation
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