8:00 -8:05

Opening and Welcome

8:05 – 8:50

Keynote Talk: Latent Causal Graph Identification

Prof. Biwei Huang, University of California San Diego (UCSD)

8:50 – 9:10

Causally Learning an Optimal Rework Policy

Oliver Schacht, Sven Klaassen, Martin Spindler, Philipp Schwarz, Daniel Grünbaum and Sebastian Imhof

9:10 – 9:30

Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution

Lu Wang, Jindong Wang, Yidong Wang and Xing Xie

9:30 – 9:50

-------- Coffee Break --------

9:50 – 10:35

Keynote Talk: Achieving causal fairness in bandit based recommendation

Prof. Xintao Wu, University of Arkansas

10:35 – 10:55

Stable Prediction on Graphs with Agnostic Distribution Shifts

Shengyu Zhang, Kun Kuang, Fuli Feng, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang and Fei Wu

10:55 – 11:15

Leveraging covariate adjustments at scale in online A/B testing

Lorenzo Masoero, Doug Hains and James McQueen

11:15 – 11:35

Optimizing Dynamic Antibiotic Treatment Strategies against Invasive Methicillin-Resistant Staphylococcus Aureus Infections using Causal Survival Forests and G-Formula on Statewide Electronic Health Record Data

Inyoung Jun, Scott A. Cohen, Sarah E. Ser, Simone Marini, Robert J. Lucero, Jiang Bian and Mattia Prosperi

11:35 – 11:55

Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments

Ruoxuan Xiong, Alex Chin and Sean Taylor

11:55 – 12:00

Closing