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因果推斷近年來(lái)取得了持續(xù)而穩(wěn)步的發(fā)展，相關(guān)方法體系不斷完善，應(yīng)用范圍也在不斷拓展。隨著人工智能技術(shù)的快速演進(jìn)，因果推斷正與人工智能深度融合，在提升人工智能系統(tǒng)的可信性、穩(wěn)健性與可解釋性方面發(fā)揮著越來(lái)越重要的作用。作為重要的數(shù)據(jù)分析工具之一，因果推斷為理解和分析大型語(yǔ)言模型等復(fù)雜智能系統(tǒng)提供了新的研究視角，并在科學(xué)、技術(shù)和工業(yè)領(lǐng)域等多個(gè)領(lǐng)域得到廣泛應(yīng)用。盡管在多源異構(gòu)數(shù)據(jù)整合、因果結(jié)論穩(wěn)健性等方面仍面臨挑戰(zhàn)，因果推斷已逐步從以理論研究為主的學(xué)術(shù)方向，發(fā)展成為支持科學(xué)研究和實(shí)際決策的重要方法，在學(xué)術(shù)界和產(chǎn)業(yè)界均受到高度關(guān)注。

泛太平洋因果推斷大會(huì)（Pacific Causal Inference Conference, PCIC）是自2019年起由北京大學(xué)講席教授、北京大學(xué)公共衛(wèi)生學(xué)院生物統(tǒng)計(jì)系系主任、北京大學(xué)北京國(guó)際數(shù)學(xué)研究中心生物統(tǒng)計(jì)和信息研究室主任周曉華博士等發(fā)起的因果科學(xué)領(lǐng)域一年一度的學(xué)術(shù)盛會(huì)。PCIC致力于探討因果推斷在不同領(lǐng)域的最新進(jìn)展，自2019年至2025年，PCIC已在北京、上海成功舉辦7屆，逐步發(fā)展成為因果推斷領(lǐng)域具有重要影響力的學(xué)術(shù)會(huì)議。

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.

會(huì)議基本信息

會(huì)議名稱(chēng)：第八屆泛太平洋因果推斷大會(huì) （PCIC 2026）

會(huì)議時(shí)間：2026年7月18日-19日

會(huì)議地點(diǎn)：中國(guó)，天津，南開(kāi)大學(xué)

會(huì)議目標(biāo)：為持續(xù)促進(jìn)因果推斷領(lǐng)域的學(xué)術(shù)交流、探索理論前沿及實(shí)踐應(yīng)用，推動(dòng)因果推斷研究成果在各學(xué)科領(lǐng)域的轉(zhuǎn)化應(yīng)用。PCIC 2026將作為一個(gè)國(guó)際性的學(xué)術(shù)平臺(tái)，匯聚因果領(lǐng)域全球頂尖專(zhuān)家學(xué)者，促進(jìn)跨學(xué)科的合作，推動(dòng)因果推斷理論的發(fā)展及其在各行業(yè)中的創(chuàng)新應(yīng)用。

Conference Information

Conference Name:

The 8th Pacific Causal Inference Conference, PCIC 2026

Conference Dates: July 18-19, 2026

Conference Venue：Nankai University, Tianjin, 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.

會(huì)議歷史/Conference History

更多會(huì)議歷史請(qǐng)查看PCIC過(guò)往官網(wǎng)鏈接：

For more information on past PCIC, please refer to the official website:

2019: http://www.conference.bicmr.pku.edu.cn/meeting/index?id=74

2020: http://www.conference.bicmr.pku.edu.cn/meeting/index?id=84

2021: http://www.conference.bicmr.pku.edu.cn/meeting/index?id=97

2022: http://www.conference.bicmr.pku.edu.cn/meeting/index?id=101

2023: http://www.conference.bicmr.pku.edu.cn/meeting/index?id=109

2024: https://www.spco.cc/pcic/

2025:https://www.spco.cc/pcic2025

組織單位/Organizing Institutions

主辦單位/Organizers

南開(kāi)大學(xué)統(tǒng)計(jì)與數(shù)據(jù)科學(xué)學(xué)院

School of Statistics and Data Science, Nankai University

北京大學(xué)公共衛(wèi)生學(xué)院生物統(tǒng)計(jì)系

Department of Biostatistics, School of Public Health, Peking University

協(xié)辦單位/Co-organizers

中國(guó)現(xiàn)場(chǎng)統(tǒng)計(jì)研究會(huì)生物醫(yī)療統(tǒng)計(jì)分會(huì)

Chinese Association for Applied Statistics-Biostatistics

中國(guó)數(shù)學(xué)會(huì)醫(yī)學(xué)數(shù)學(xué)專(zhuān)委員會(huì)

CMS-Mathematics in Medicine

北京國(guó)際數(shù)學(xué)研究中心

Beijing International Center for Mathematical Research

組委會(huì)/Organizing Committee

Committee Chair

Xiao-Hua Zhou, PKU Endowed Chair Professor, Peking University, China

Committee Members

Robin Evans, Professor, University of Oxford, UK

Fang Han, Job & Gertrude Tamaki Endowed Professor, University of Washington, USA

Jinzhu Jia, Associate Professor, Peking University, China

Theis Lange, Professor, University of Copenhagen, Danmark

Thomas S Richardson, Professor, University of Washington, USA

Don B. Rubin, Emeritus Professor, Harvard University, USA

Linbo Wang, Associate Professor, University of Toronto, Canada

Lu Wang, Professor, University of Michigan, USA

Ting Ye, Assistant Professor, University of Washington, USA

Fabrizia Mealli, Professor, European University Institute, Italy

Satoshi Hattoris, Professor, Osaka University, Japan

Shu Yang, Professor, NC State University, USA

Diaz Ordaz Karla, Professor, University College London, UK

Mingming Gong, Associate Professor, The University of Melbourne, Australia

Lan Wang, Centennial Endowed Chair Professor, University of Miami, USA

參會(huì)類(lèi)型/Participation Type

1、聽(tīng)眾參會(huì)

繳費(fèi)注冊(cè)成為付費(fèi)聽(tīng)眾，參加兩天（7月18-19日）會(huì)議。

2、口頭報(bào)告參會(huì)

學(xué)生：注冊(cè)后提交全文及學(xué)生證明，優(yōu)秀文章可參與評(píng)獎(jiǎng)。

非學(xué)生：注冊(cè)后提交摘要

3、海報(bào)展示參會(huì)

主要面向?qū)W生，繳費(fèi)注冊(cè)后提交摘要

注：口頭報(bào)告參會(huì)及海報(bào)展示參會(huì)全文及摘要投稿截止日期2026年4月30日

4、短課參會(huì)

報(bào)名參加因果推斷短期培訓(xùn)課程，參加7月17日下午培訓(xùn)課程

注：大會(huì)參會(huì)（聽(tīng)眾/口頭報(bào)告/海報(bào)）與短課參會(huì)為兩個(gè)獨(dú)立活動(dòng)，可重復(fù)報(bào)名并同時(shí)參加。

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.

會(huì)議日程/Conference Schedule

以上日程為暫定計(jì)劃，詳細(xì)內(nèi)容將實(shí)時(shí)補(bǔ)充更新
The above schedule is provisional. Detailed arrangements will be supplemented and updated in real time.

短課介紹/Short Course

課程簡(jiǎn)介

本短課將以因果推斷的統(tǒng)計(jì)學(xué)基礎(chǔ)為起點(diǎn)，系統(tǒng)講解因果科學(xué)從傳統(tǒng)統(tǒng)計(jì)方法到智能科學(xué)前沿的發(fā)展脈絡(luò)。因果推斷擁有堅(jiān)實(shí)的理論基礎(chǔ)：在Neyman—Rubin潛在結(jié)果框架下，因果推斷主要圍繞因果效應(yīng)的定義、識(shí)別、估計(jì)及推斷展開(kāi)。因果圖作為描述多變量間相互作用機(jī)制的關(guān)鍵工具，能夠幫助我們深刻理解因果關(guān)系的機(jī)制，特別是在干預(yù)條件下如何傳遞因果作用。

因果推斷目前已廣泛應(yīng)用于生物統(tǒng)計(jì)等眾多領(lǐng)域，其中混雜因素的處理是核心難點(diǎn)之一。針對(duì)觀(guān)察性研究，本課程將根據(jù)不同的數(shù)據(jù)類(lèi)型和生成機(jī)制，介紹相應(yīng)的因果推斷方法。比如：在完全隨機(jī)化不可行的場(chǎng)景下，如何通過(guò)回歸、加權(quán)與雙穩(wěn)健方法有效估計(jì)因果效應(yīng)，以及怎樣選擇最優(yōu)估計(jì)量；在結(jié)局受處理后事件影響時(shí)，如何運(yùn)用中介分析分解不同路徑上的因果效應(yīng)，并處理事件發(fā)生時(shí)間型中介與結(jié)局的復(fù)雜問(wèn)題；在結(jié)局無(wú)法直接定義的情況下，如何借助主分層技術(shù)識(shí)別科學(xué)目標(biāo)人群及其因果效應(yīng)；面對(duì)不可控的未觀(guān)測(cè)混雜，如何利用工具變量、陰性對(duì)照變量等方法進(jìn)行因果識(shí)別。此外，課程還將介紹歸因分析技術(shù)，即如何根據(jù)已知結(jié)果推斷可能的原因。

在人工智能時(shí)代背景下，因果推斷與機(jī)器學(xué)習(xí)日益融合，課程將探討深度學(xué)習(xí)等現(xiàn)代方法在因果效應(yīng)估計(jì)中的應(yīng)用，包括復(fù)雜場(chǎng)景下未觀(guān)測(cè)混雜的處理及因果效應(yīng)的泛化能力。最后，我們將結(jié)合實(shí)際案例，介紹因果推斷在計(jì)算機(jī)視覺(jué)、自然語(yǔ)言處理、互聯(lián)網(wǎng)推薦系統(tǒng)、大型語(yǔ)言模型等先進(jìn)領(lǐng)域的多樣化應(yīng)用，幫助學(xué)員全面了解因果科學(xué)的理論基礎(chǔ)與創(chuàng)新實(shí)踐。

授課老師

• 周曉華，北京大學(xué)講席教授

• 鄧宇昊，福瑞德·哈金森癌癥研究中心博士后研究員

• 鄭淳元，北京大學(xué)博士研究生

課程大綱

Introduction

This short course begins with the statistical foundations of causal inference and systematically explores the development of causal science, from traditional statistical methods to the cutting edge of intelligent science. Causal inference is built on a solid theoretical basis: under the Neyman–Rubin potential outcomes framework, the main topics include the definition, identification, estimation, and inference of causal effects. Causal diagrams serve as essential tools for describing the mechanisms of interaction among multiple variables, helping us gain a deep understanding of how causal relationships operate, especially how causal effects are transmitted under interventions.

Causal inference has been widely applied in biostatistics and many other fields, with the challenge of confounding being a central focus. For observational studies, this course will introduce suitable causal inference methods based on different data types and data-generating mechanisms. For instance: when complete randomization is infeasible, how to effectively estimate causal effects using regression, weighting, and doubly robust methods, and how to choose optimal estimators; when outcomes are affected by post-treatment events, how to use mediation analysis to decompose causal effects along different pathways, and how to handle time-to-event mediators and outcomes; when the outcome cannot be directly defined, how to use principal stratification to identify target populations and causal effects; and when unmeasured confounding cannot be controlled, how to identify causal effects using instrumental variables and negative control variables. Additionally, the course covers attribution analysis, which aims to infer possible causes based on known results.

In the era of artificial intelligence, causal inference increasingly interacts with machine learning. This course will also examine applications of modern methods such as deep learning in causal effect estimation, including strategies for dealing with unmeasured confounding in complex scenarios and enhancing the generalizability of causal inference. Finally, through practical case studies, the course will illustrate the diverse applications of causal inference in cutting-edge fields such as computer vision, natural language processing, internet recommendation systems, and large language models, equipping participants with a comprehensive understanding of both the theoretical foundations and innovative practices in causal science.

Short Course Instructors

• Xiao-Hua Zhou, PKU Endowed Chair Professor, Peking University

• Yuhao Deng, Postdoctoral Fellow, Fred Hutch Cancer Center

• Chunyuan Zheng, Ph.D. Student, Peking University

Short Course Outline

會(huì)議注冊(cè)/Registration

注冊(cè)費(fèi)用/Registration Fees

無(wú)論參會(huì)類(lèi)型，注冊(cè)費(fèi)用統(tǒng)一按參會(huì)人員身份（學(xué)生/非學(xué)生）收取。

Regardless of the participation type, registration fees are charged based on participant status (student / non-student)

報(bào)名方式/Registration Method

會(huì)議注冊(cè)（觀(guān)眾、口頭報(bào)告、海報(bào)展示）：

第一步：繳費(fèi)注冊(cè)

請(qǐng)先掃描二維碼完成會(huì)議繳費(fèi)注冊(cè)，并妥善保存付款截圖，后續(xù)將用于上傳核驗(yàn)。

第二步：登錄系統(tǒng)并提交材料

請(qǐng)?jiān)L問(wèn)以下注冊(cè)鏈接：

https://www.meta-conference.cc/index/index/detail/id/89.html

注冊(cè)用戶(hù)名并登錄系統(tǒng)，按要求填寫(xiě)個(gè)人基本信息。

1. 在支付方式中請(qǐng)選擇 Bank Transfer，并上傳第一步中保存的付款截圖。

請(qǐng)注意：在填寫(xiě)信息的過(guò)程中

• Paper ID：請(qǐng)?zhí)顚?xiě) N/A
  

• Dining：7月18-19日提供午餐，請(qǐng)勾選 Regular Meal

2. 提交后，訂單狀態(tài)將顯示為 Pending。會(huì)務(wù)組在確認(rèn)收到款項(xiàng)后，會(huì)將訂單狀態(tài)更新為Complete。

3. 在此期間，您可登錄注冊(cè)后臺(tái)，在My Registration頁(yè)面中，根據(jù)參會(huì)類(lèi)型（口頭報(bào)告 / 海報(bào)展示）上傳相應(yīng)的摘要或全文。

說(shuō)明：

如您無(wú)法通過(guò)掃碼方式完成支付，可使用Bank Transfer頁(yè)面中提供的銀行賬戶(hù)信息進(jìn)行轉(zhuǎn)賬，并在系統(tǒng)中上傳相應(yīng)的付款憑證。

短課注冊(cè)：

請(qǐng)?jiān)L問(wèn)以下鏈接完成報(bào)名:

https://meta-conference.cc/index/index/detail/id/90.html

1.請(qǐng)?jiān)?strong>Meta-Conference注冊(cè)網(wǎng)站完成用戶(hù)注冊(cè)（如尚無(wú)賬戶(hù)）
2.完成注冊(cè)后，請(qǐng)選擇因果推斷短課程進(jìn)行報(bào)名
3.請(qǐng)根據(jù)提示如實(shí)填寫(xiě)所有帶星號(hào)（*）的必填信息，包括：
·參會(huì)人姓名
·聯(lián)系電話(huà)
·電子郵箱
·所屬單位
·Paper ID：請(qǐng)?zhí)顚?xiě) N/A
4. Attendee Type：短課僅支持線(xiàn)下參會(huì)，無(wú)需勾選此項(xiàng)
5. Dining：PCIC 2026短課不提供餐食，無(wú)需勾選此項(xiàng)
6. Attendee's Name：請(qǐng)?zhí)顚?xiě)參會(huì)人員姓名，英文格式
完成全部信息填寫(xiě)后，請(qǐng)點(diǎn)擊 Submit Payment 跳轉(zhuǎn)至付款頁(yè)面，付款成功后會(huì)議秘書(shū)將與您取得聯(lián)系確認(rèn)報(bào)名信息。

Conference Registration (Listener / Oral Presentation / Poster Presentation):

Step 1: Payment and Registration

Please scan the QR code to complete the conference payment and registration. Kindly save a screenshot of the payment confirmation, as it will be required for later verification.

Step 2: System Login and Submission

Please visit the following registration link:

https://www.meta-conference.cc/index/index/detail/id/89.html

Create a user account and log in to the system. Fill in the required personal information.

Please note the following when filling in the information:

• Paper ID: Please enter N/A.

• Dining: Lunch will be provided on July 18–19. Please select the Regular Meal.

1. When selecting the payment method, please choose Bank Transfer and upload the payment screenshot saved in Step 1.

2. After submission, the order status will be marked as Pending. Once the organizing committee confirms receipt of the payment, the status will be updated to Complete.

3. During this period, you may log in to the registration system and, under My Registration, upload the required abstract or full paper according to your participation type (oral presentation or poster presentation).

Note:

If you are unable to complete the payment via QR code, please use the bank account information provided under Bank Transfer, complete the transfer manually, and upload the payment proof to the system.

Short Course Registration:

https://meta-conference.cc/index/index/detail/id/90.html

Participation Steps:

1. Create a user account on the Meta-conference website if you do not already have one
2. Proceed to register for the short course
3. Complete all required fields (*) with accurate information, including:
· Full name of attendee
· Phone number
· Email address
· Affiliation
· Country
· Paper ID: Please enter “N/A”
4. Attendee Type: Only in-person participation, no selection is needed
5. Dining: Since no meals will be provided for the short course, no selection is needed
6. Attendee’s Name: Fill in the attendee’s name in English format.
7. After completing all information, click “Submit Payment” to proceed to the payment page.
Once payment is successfully processed, the conference secretary will contact you to confirm your registration details.

聯(lián)系方式/Contact

更多詳細(xì)會(huì)議信息，請(qǐng)查看會(huì)議網(wǎng)站：https://www.spco.cc/pcic2026

For more detailed conference information, please visit the conference website: https://www.spco.cc/pcic2026

組委會(huì)負(fù)責(zé)人：陳博 (Bo Chen)

電子郵件：[email protected]

秘書(shū)處負(fù)責(zé)人：紀(jì)曉宇 (Jenny Ji)

電話(huà)（微信）：15618780723
??電子郵件：[email protected]

秘書(shū)處負(fù)責(zé)人：范添瑞 (Damone Fan)

電話(huà)（微信）：13310183307
??電子郵件：[email protected]