【Online Conference】The 2020 Pacific Causal Inference Conference
主讲人： Xiao-Hua(Andrew) Zhou (BICMR)
活动时间： 从 2020-09-26 08:00 到 2020-09-27 08:00
场地： Online
【Tentative Schedule】The 2020 Pacific Causal Inference Conference
9/26-9/27.2020
Beijing Local Time
Host:Peking University
Description:The goal of causal inference is to combine external knowledge and study design to draw a causal conclusion between variables. It has gained popularity in fields including statistics, biostatistics, biomedical science, computer science, economics, epidemiology, and various social sciences. This conference will focus on the latest development in the statistic on causal inference in biostatistics.
The program of the conference will target university-based statisticians and industry-based statisticians. The conference follows last year’s successful causal inference conference in Beijing. Due to the COVID-19，the 2020 Pacific Causal Inference Conference will go virtual this year, which will take place between Sept 26th and Sept 27th.
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Each day of the conference will contain three sessions, with every session is split into 4 or 6 tracks. Each track is conducted via Zoom
Time Zone
PST(San Francisco)
CST(Chicago)
Eastern Time (New York)
Europe
UK
Beijing Time
UTC-7
UTC-5
UTC-4
UTC+1
0
UTC+8
Session 1
Fri 5pm-8pm
Fri 7pm-10pm
Fri 8pm-11pm
Sat 2am-5am
Sat 1am-4am
Sat 8am-11am
Session 2
Fri/Sat 10pm-1am
Sat 0-3am
Sat 1am-4am
Sat 7am-10am
Sat 6am-9am
Sat 1pm-4pm
Session 3
Sat 5am-7am
Sat 7am-9am
Sat 8am-10am
Sat 2pm-4pm
Sat 1pm-3pm
Sat 8pm-10pm
Session 4
Sat 5pm-8pm
Sat 7pm-10pm
Sat 8pm-11pm
Sun 2am-5am
Sun 1am-4am
Sun 8am-11am
Session 5
Sat/Sun 10pm-1am
Sun 0-3am
Sun 1am-4am
Sun 7pm-10pm
Sun 6pm-9pm
Sun 1pm-4pm
Session 6
Sun 5am-7am
Sun 7am-9am
Sun 8am-10am
Sun 2pm-4pm
Sun 1pm-3pm
Sun 8pm-10pm
Main Conference, Sept 26th-27th, 2020
All times are UTC+8 (Beijing , summertime/Day-light saving Time)
|
DATE |
TIME |
SESSION |
SESSION Chair |
|
Sat. Sept 26th |
8:00-8:30am UTC+8 |
Welcome Remark |
Xiao-Hua Zhou |
|
Sat. Sept 26th |
8:30-10:50am UTC+8 |
Session ONE |
Peng Ding |
|
Sat. Sept 26th |
1:00-3:45pm UTC+8 |
Session TWO |
Xiao-Hua Zhou |
|
Sat. Sept 26th |
8:00-9:55pm UTC+8 |
Session THREE |
Theis Lange |
|
Sun. Sept 27th |
8:00-10:45am UTC+8 |
Session FUOR |
Linbo Wang |
|
Sun. Sept 27th |
1:00-3:45pm UTC+8 |
Session FIVE |
TBA |
|
Sun. Sept 27th |
8:00-9:55pm UTC+8 |
Kun Zhang |
Day one 9/26:
|
|
Sept 26th |
||
|
Session 1 |
Chair: Peng Ding |
||
|
8:15-8:30 |
Welcome Remark |
Xiao-Hua Zhou |
|
|
8:30-8:55 |
1 Don Rubin (Boston) |
TBA |
|
|
8:55-9:20 |
2 Donglin Zeng (UNC) |
Improve Learning Trial-Based Treatment Strategies Using Electronic Health Records |
|
|
9:20-9:45 |
3 Linbo Wang (UT) |
Causal Ball Screening: Outcome Model-Free Causal Inference with Ultra-High-Dimensional Covariates |
|
|
Break!(15mins) |
|||
|
10:00-10:25 |
4 James M Robins(Harvard) |
An Interventionist Approach to Mediation Analysis |
|
|
10:25-10:50 |
5 Zhichao Jiang (UM-Amherst) |
Experimental Evaluation of Computer-Assisted Human Decision Making |
|
|
Session 2 |
Chair: Xiao-Hua Zhou |
||
|
13:00-13:25 |
6 Peng Ding (UC-Berkerly) |
Randomization Tests for Weak Null Hypotheses |
|
|
13:25-13:50 |
7 Lexin Li (UC-Berkerly) |
Testing Mediation Effects Using Logic of Boolean Matrices |
|
|
13:50-14:15 |
8 Lihua Lei (Stanford) |
Conformal Inference of Counterfactuals and Individual Treatment Effects |
|
|
Break!(15mins) |
|||
|
14:30-14:55 |
9 Lin Liu (SJTU) |
On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning |
|
|
14:55-15:20 |
10 Anqi Zhao (NUS) |
Reconciling design-based and model-based inference for split-plot designs |
|
|
15:20-15:45 |
11 TBA |
TBA |
|
|
Session 3 |
Chair: Theis Lange |
||
|
20:00-20:25 |
12 Shu Yang (NCSU) |
Improved Inference for Heterogeneous Treatment Effects Using Real-World Data Subject to Hidden Confounding |
|
|
20:25-20:50 |
13 Elizabeth L. Ogburn (JHU) |
Social network dependence and unmeasured confounding |
|
|
Break!(15mins) |
|||
|
21:05-21:30 |
14 Qingyuan Zhao (Cambridge) |
Discovering mechanistic heterogeneity using Mendelian randomization |
|
|
21:30-21:55 |
15 Bernhard Schölkopf (Germany) |
TBA |
|
Day Two 9/27:
|
|
Sept 27th |
||
|
Session 4 |
Chair: Linbo Wang |
||
|
8:00-8:25 |
16 Ilya Shpitser (JHU) |
Identification and estimation of causal parameters via a modified factorization of a graphical model |
|
|
8:25-8:50 |
17 Lu Wang (UM) |
New statisticaly learning methods for evaluating the optimal dynamic treatment regimes leading toward personalized health care |
|
|
8:50-9:15 |
18 Walter Dempsey (UM) |
Micro-randomized trials and cluster-level treatment effect heterogeneity |
|
|
Break!(15mins) |
|||
|
9:30-9:55 |
19 Kun Zhang (CMU) |
Causal discover and domain adaptation with independent changes |
|
|
9:55-10:20 |
20 Peter Spirtes (CMU) |
Assumptions for Discovering Causal Structures from Observational Data |
|
|
10:20-10:45 |
21 Lu Mao (UW-Madison) |
Wilcoxon-Mann-Whitney statistics in randomized trials with non-compliance |
|
|
Session 5 |
Chair: TBA |
||
|
13:00-13:25 |
22 Richard Guo & Ema Perković (Seattle) |
Efficient Least Squares for Estimating Total Causal Effects |
|
|
13:25-13:50 |
23 Fei Wu (ZJU) |
Big data intelligence: from correlation discovery to casual reasoning |
|
|
13:50-14:15 |
24 Peng Cui (THU) |
Stable Learning: The Convergence of Causal Inference and Machine Learning |
|
|
Break!(15mins) |
|||
|
14:30-14:55 |
25 Xiao-Hua Zhou (PKU) |
Causal Inference in Observational Data with High-Dimensional Covariates |
|
|
14:55-15:20 |
26 Zhenhua Lin (NUS) |
Causal Inference with Manifold-valued Outcomes |
|
|
15:20-15:45 |
27 TBA |
TBA |
|
|
Session 6 |
Chair: TBA |
||
|
20:00-20:25 |
28 Theis Lange (Copenhagen) |
Bounding casual effect estimates from IV studies |
|
|
20:25-20:50 |
29 Torben Martinussen (Copenhagen) |
Causal Inference and Competing Risk Data |
|
|
Break!(15mins) |
|||
|
21:05-21:30 |
30 Zhiqiang Tan (RU) |
Doubly Robust Semiparametric Inference Using Regularized Calibrated Estimation with High-dimensional Data |
|
|
21:30-21:55 |
31 Ingeborg Wernbaum (Sweden) |
Calibration/entropy balancing for average causal effects - a comparative study (Joint work with David Källberg and Emma Persson) |
|
ZOOM Arrangement:
Theme：【Online】The 2020 Pacific Causal Inference Conference
Date：Sept 26th to Spet 27th , 2020, Beijing Time
Conference ID：644 7728 2320
PSWD: 478893
Registration：
https://www.wjx.top/m/86188475.aspx
（Registration fees are waived for attending the conference, but you need to register for attendance）
For more info: http://conference.bicmr.pku.edu.cn/meeting/index?id=84
