معرفی
Kelly Zhang is an Assistant Professor in the Department of Mathematics (Statistics Section) at Imperial College London, and a faculty member of the interdisciplinary AI initiative I-X. She holds a PhD in Computer Science from Harvard University, advised by Susan Murphy and Lucas Janson, supported by an NSF Graduate Fellowship and Siebel Scholar recognition.
- Research focus: Adaptive experimentation, reinforcement learning, and statistical inference
- Recent contributions: Frameworks for contextual Thompson sampling, delayed reward optimization, and autoregressive exploration
- Conference involvements: NeurIPS, INFORMS, IEEE-EMBS, IMS-Bernoulli, RLC, JSM
Her work bridges machine learning and statistics with applications in health informatics, podcast recommendation systems, and econometric society interdisciplinary research. She has collaborated with leading researchers including Daniel Russo, Hongseok Namkoong, and Sasha Rush.
Scientific Awards:
- NSF Graduate Fellowship
- Siebel Scholar (2023)
Her statistical inference work has been published in NeurIPS (2020, 2021) and applied to both academic and industry settings at Apple HealthAI, Facebook AI Research, and eBay.
