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Shuyang Du

Shuyang Du
0 BLOG ARTICLES 2 RESEARCH PAPERS
Shuyang is a data scientist at Uber Marketplace, working research and application of topics including causal machine learning, deep learning and machine learning system design.

Research Papers

Heterogeneous Causal Learning for Effectiveness Optimization in User Marketing

W. Y. Zou, S. Du, J. Lee, J. Pedersen
User marketing is a key focus of consumer-based internet companies. Learning algorithms are effective to optimize marketing campaigns which increase user engagement, and facilitates cross-marketing to related products. By attracting users with rewards, marketing methods are effective to boost user activity in the desired products. Rewards incur significant cost that can be off-set by increase in future revenue. [...] [PDF]
2020

Improve User Retention with Causal Learning

S. Du, J. Lee, F. Ghaffarizadeh
User retention is a key focus for consumer based internet companies and promotions are an effective lever to improve retention. However, companies rely either on non-causal churn prediction to capture heterogeneity or on regular A/B testing to capture average treatment effect. In this paper, we propose a heterogeneous treatment effect optimization framework to capture both heterogeneity and causal effect. [...] [PDF]
SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019

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