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