In recent years, causal inference has experienced sustained and steady development. Its methodological framework has been continuously refined, and its range of applications has expanded significantly. With the rapid advancement of artificial intelligence (AI) technologies, causal inference is becoming deeply integrated with AI, playing an increasingly important role in enhancing the reliability, robustness, and interpretability of AI systems. As a key data analysis tool, causal inference provides new perspectives for understanding and analyzing complex intelligent systems such as large language models, and has been widely applied across science, technology, and industry. Although challenges remain—particularly in areas such as multi-source heterogeneous data integration and the robustness of causal conclusions—causal inference has gradually evolved from a predominantly theoretical academic pursuit into a vital methodology supporting scientific research and practical decision-making, attracting growing attention from both academia and industry.
The Pacific Causal Inference Conference (PCIC), established in 2019 by Dr. Xiao-Hua Zhou, Chair Professor at Peking University, Chair of the Department of Biostatistics at the School of Public Health, and Director of the Biostatistics and Informatics Research Center at the Beijing International Center for Mathematical Research, has become an annual academic event in the causal science community. Dedicated to exploring the latest developments in causal inference across various domains, PCIC has successfully hosted seven editions in Beijing and Shanghai from 2019 to 2025.
Conference Information
Conference Name: The 8th Pacific Causal Inference Conference, PCIC 2026
Conference Dates: July 18–19, 2026
Conference Venue: Chern Institute of Mathematics, Nankai University, China
Conference Objectives: To promote ongoing academic exchange, explore theoretical advancements, and enhance the practical application of causal inference. PCIC 2026 will bring together leading experts to foster cross-disciplinary collaboration, advance research, and drive innovation across industries.
Participation Type
1. Listener Participation: register as a listener and attend the two-day conference (July 18–19).
2. Oral Presentation Participation:
Students: After registration, submit a full paper along with valid student certification. Outstanding papers will be considered for awards.
Non-students: After registration, submit an abstract.
3. Poster Presentation Participation:
Primarily for students. After paid registration, participants submit an abstract.
Note: The submission deadline for full papers and abstracts for oral presentations and poster presentations is April 30, 2026.
4. Short Course Participation:
Participants register for a short course on causal inference, held on the afternoon of July 17.
Note: Conference participation (audience/oral presentation/poster) and short course participation are two independent activities. Participants may register for both and attend concurrently.
Jul 18
2026
Jul 19
2026
Abstract Submission Deadline
Final Paper Deadline
Contribution Submission Deadline
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