The Pacific Causal Inference Conference (PCIC) embarked on its journey with the inaugural edition, PCIC2019, which unfolded at the Lecture Hall of Peking University on May 11-12, 2019. This event, featuring keynote speeches by more than 10 experts, set the tone for subsequent conferences, laying the foundation for fruitful discussions and collaborations in the realm of causal inference.


The momentum continued with PCIC2020, the second edition held at Peking University on September 26-27, 2020. With over 30 speakers representing esteemed institutions such as the University of Michigan, the conference fostered a dynamic environment, attracting more than 100 participants. This edition solidified PCIC's position as a premier platform for the exchange of ideas in the evolving field.


In 2021, PCIC returned to Peking University for its third edition, PCIC2021, held on September 11-12. The event featured 28 speakers from diverse global institutions, including Duke University, Oxford University, and Carnegie Mellon University. The conference's expanding reach and diverse lineup underscored its significance in the global causal inference landscape.


The fourth edition, PCIC2022, held on September 17-18, 2022, marked a pivotal moment for the conference. With 37 invited guests and the introduction of the Huawei Causal Inference Challenge, PCIC2022 attracted over 1,000 participants and garnered a substantial live stream audience of more than 30,000. This edition showcased the conference's growing influence and its embrace of innovative initiatives.


PCIC2023, the fifth edition, held on September 16-17, 2023, further solidified the conference's standing. Featuring over 50 speakers, a pre-conference short course, and interactive sessions for researchers, this edition demonstrated PCIC's commitment to continuous growth and inclusivity within the dynamic field of causal inference. The evolution of PCIC across these five editions highlights its role as a pivotal platform for advancing knowledge and collaboration in the intricate realm of causal inference.