Construction of Generalized Causal Forests and Their Application in Online Transaction Markets
On November 26, 2022, at the DataFun Summit 2022 online causal inference conference, PhD candidate Wan Shu from Arizona State University will present a talk titled “Construction of Generalized Causal Forests and Their Application in Online Transaction Markets,” covering treatment effect estimation, model building, performance comparison, and practical use cases.
On November 26, 2022, from 13:30 to 16:50, the DataFun Summit 2022: Online Causal Inference Summit will feature a presentation by Arizona State University PhD candidate Wan Shu on the topic “Construction of Generalized Causal Forests and Their Application in Online Transaction Markets.”
Speaker Bio: Wan Shu is a first‑year PhD student in Data Science and Analytics Engineering at Arizona State University, focusing on causal inference and physics‑informed machine learning. She previously worked at Didi Chuxing’s supply‑demand strategy tech team, developing price elasticity models and the price experiment platform, and contributed to the development and deployment of the Generalized Causal Forest model.
Talk Title: Construction of Generalized Causal Forests and Their Application in Online Transaction Markets
Outline:
1. Importance of treatment‑effect estimation in transaction‑market strategies.
2. What is a Generalized Causal Forest and how it is constructed.
3. Performance of Generalized Causal Forests compared with other models.
Audience Benefits:
1. How to estimate continuous non‑linear treatment effects.
2. How to build a Generalized Causal Forest.
3. Real‑world applications of Generalized Causal Forests.
How to Participate?
About DataFun: DataFun focuses on sharing and exchanging big‑data and AI technologies. Founded in 2017, it has held over 100 offline and 100 online salons, forums, and summits across major Chinese cities, involving more than 2,000 experts and scholars. Its WeChat public account, DataFunTalk, has published over 800 original articles, amassed millions of reads, and gained over 150,000 targeted followers.
DataFunTalk
Dedicated to sharing and discussing big data and AI technology applications, aiming to empower a million data scientists. Regularly hosts live tech talks and curates articles on big data, recommendation/search algorithms, advertising algorithms, NLP, intelligent risk control, autonomous driving, and machine learning/deep learning.
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