Song Yao is a Professor of Marketing at the Olin Business School, Washington University in St. Louis. He also serves as an Amazon Scholar and is a former Principal Economist at Amazon’s Stores Economics and Science group (SEAS, formerly Core AI).

· 邮箱： [email protected]. · 电话： · 传真： · 学术网页： https://songlory.wixsite.com/songlory. · 研究方向： 创新设计与数字艺术. Innovation Design and Digital Creativity. 1. 艺术数字化（书画、电影、音乐、香气等） 2. 艺术管理（艺术品定价、...

Does Online Word-of-Mouth Increase Demand? (and How?) Evidence from a Natural Experiment.

Yao Song. University of Michigan, Ann Arbor. Verified email at umich.edu. Biostatistics. Articles Cited by Public access Co-authors. ... JN Fahmy, Y Song, L Wang, KC Chung. JAMA network open 6 (7), e2325487-e2325487, 2023. 5: 2023: Multiobjective tree-based reinforcement learning for estimating tolerant dynamic treatment regimes. Y Song, L Wang ...

I am an economist working at the intersection between economics and marketing. I am a Professor of Marketing at Olin Business School, Washington University in St. Louis. I am also an Amazon Scholar and former Principal Economist of Amazon's Stores Economics and Science team (SEAS, formerly Core AI).

2021年12月，姚颂向母校长沙市第一中学捐赠100万元，成立“清琢”基金，寄语在校同学“学会独立思考，明确人生不同时期的目标；学会调整发展方向，不断确立更高的目标，并为之而奋斗；把握好当下，珍惜时间，为未来人生发展积累能量。 ” [21] 2022年2月，姚颂向上海崇明 徐根宝足球基地 基地捐赠了50万元人民币，支持足球青训事业。 [22] [25] 2021年10月20日，入选《2021胡润U30中国创业领袖》名单。 [14] 2022年12月，入选《2022广州市番禺区·胡润U30中国创业先 …

Yao, Song, and Yuxin Chen, “The Value of Structural Estimates for Consumer Search Models.” Awarded annually by the American Marketing Association Foundation for the paper published in the Journal of Marketing Research and with the most potential to contribute to the practice of marketing research.

At Roswell Park, I lead an active population-based “dry lab” research program of molecular and genetic epidemiology that combines multi-disciplines of epidemiology, oncology, genetics, immunology, biostatistics, and bioinformatics.

Yao Song is a first-year PhD student in the Department of Biostatistics. Her research interests lie in personalized medicine, especially combining causal inference and machine learning methods to estimate dynamic treatment regimens.