You are invited to submit your full paper to PCIC2024. PCIC aims to become a premier international conference in Causal Inference and attracts world-leading scientists and engineers from a wide range of disciplines. PCIC2024 will be held as a hybrid event, allowing both onsite and online participation in Shanghai.

Topics of interest for PCIC2024 include, but are not limited to:

    T1. Frontiers in Causal Inference Theories and Methods
    Causal discovery methods
    Estimation of average causal effects
    Estimation of conditional average causal effects
    Estimation of individual causal effects and counterfactual learning
    Instrumental variable methods
    Methods for causal representation learning
    De-biasing methods based on causal inference
    Causal inference based on uncertainty
    Causal interpretability
    Causal assessment, tools, and resources
    Modeling unmeasured confounding factors in complex scenarios

    T2. Applications of Causal Inference in the Field of Artificial Intelligence
    Causal reasoning methods based on Large Language Models (LLM)
    Causal discovery methods based on Large Language Models (LLM)
    Causal natural language processing
    Causal precision medicine
    Causal recommendation systems
    Causal trustworthy learning
    Causal strategy learning
    Causal methods for addressing out-of-distribution generalization (OOD)
    Causal-based counterfactual data generation

    T3. Computational Intelligence and Causal Inference
    Unsupervised and Semi-supervised Deep Learning Connected to Causality
    Causal Generative Models for Machine Learning
    Machine Learning Algorithms for Causal Discovery
    Machine Learning Building on Causal Principles
    Reinforcement Learning and Causal Inference
    Causal inference in Natural Language Processing
    Causal Reasoning and Large Language Models
    Data Mining for Causality Methods

    T4. Specific Application of Causal Inference

    Applications in online systems (e.g. search, recommendation, ad placement)
    Applications in physical systems (e.g. cars, smart homes)
    Applications in medicine (e.g. personalized treatment, clinical trials)
    Applications in economics and political science
    Causal inference in philosophy and psychology
    Other Real-world problems for causal analysis