会议摘要（Abstract）

Causality has long been central to the human philosophical debate and scientific pursuit. Among the many relevant questions on causality, statistics arguably can contribute the most to the question of measuring the effects of “causes”, or more specifically, interventions or actions. The last two decades have witnessed an explosive growth in statistical and machine learning theory and methods for causal inference. These methods have been increasingly applied to solve real world problems in many disciplines. This workshop will focus on exchanging new developments in theory and methods as well as impactful interdisciplinary applications. Main topics will include: (i) design and analysis of complex randomized experiments; (ii) natural and quasi-experimental designs, including instrumental variables; (iii) machine learning methods for causal inference; (iv) causal inference in action; (v) accessible causal inference: software and translational work.

因果关系长期以来一直是人类哲学辩论和科学追求的核心。在许多与因果关系相关的问题中，统计学可以说在“因果”或更具体地说是干预或行动的效果测量问题上贡献最大。过去二十年，统计学和机器学习理论及方法在因果推断方面经历了爆炸性增长。这些方法被越来越多地应用于解决各学科的实际问题。本次研讨会将重点交流理论和方法的新进展以及具有影响力的跨学科应用。主要议题包括：(i) 复杂随机实验的设计和分析；(ii) 自然实验和准实验设计，包括工具变量；(iii) 因果推断的机器学习方法；(iv) 因果推断的实际应用；(v) 可访问的因果推断：软件和转化工作。

举办意义(Description of the aim)

This workshop aims to bring together a group of respected and active researchers to present their ongoing work in several most important current areas of causal inference, including complex randomized experiments, natural experiments, machine learning methods, software development, and interdisciplinary applications. It will provide an opportunity for researchers at different career stages to exchange ideas with internationally leading experts and foster new collaborations in an intimate environment. In particular, the workshop will provide a platform for young researchers to showcase their achievements and network. Overall, the workshop is expected to contribute to building and strengthening the causal inference community in China.

本次研讨会旨在汇聚一组受尊敬且活跃的研究人员，展示他们在因果推断几个重要领域的最新工作，包括复杂随机实验、自然实验、机器学习方法、软件开发和跨学科应用。研讨会将为不同职业阶段的研究人员提供与国际领先专家交流想法的机会，并在亲密的环境中促进新合作。特别地，研讨会将为年轻研究人员提供展示成果和建立联系的平台。总体而言，研讨会预计将有助于建立和加强中国的因果推断社区。