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Causal Science Conference 2023

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Join the Stanford Causal Science Center (SC²) on Thursday, November 16, 2023, for a one-day conference at Fisher Conference Center in Arrillaga Alumni Center.

The program consists of presentations and posters by Stanford graduate students and postdoctoral scholars working on a breadth of causal science topics, from methodology to applications.  This convening offers an opportunity for the community to learn more about the breadth of work happening at Stanford, to forge new connections, and to help shape a path for the future success of SC².

Register to attend!

Agenda

9:00-9:15WelcomeGuido Imbens
   
9:15-10:15Theme: EconometricsChair: Maya Rossin-Slater
 Amar VenugopalDouble and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control
 Erik SverdrupQini Curves for Multi-Armed Treatment Rules
 Junting DuanCausal inference for large dimensional non-stationary factor models with two-way endogenous treatment
 Timothy SudijonoInference for Synthetic Controls via Refined Placebo Tests
   
10:15-10:35Break 
   
10:35-11:35Theme: ApplicationsChair: Dominik Rothenhaeusler
 Anna LukkarinenDo sustainability signals attract crowdinvestors? Evidence from a randomized field experiment
 Felix MichalikThe effect of herpes zoster vaccination on the occurrence of deaths due to dementia in England and Wales
 Chi Heem WongCausal inference in supply chain management
 Zachary KaufmanA Data-Driven Approach to Climate Change Attribution: Inferring Causal Mechanisms in Observation-Based Time Series
   
11:35-12:35Lunch 
   
12:35-1:35Theme: Emerging MethodsChair: Vasilis Syrgkanis
 Yuchen HuA Decision-Theoretic Framework for Sample Selection in Randomized Experiments
 Katherine TsaiProxy Methods for Domain Adaptation
 Yash ChandakAdaptive Instrument Design for Indirect Experiments
 Maggie WangDesigning Randomized Experiments for Behavioral Interventions Under Interference and Context-Dependence
   
1:35-1:55Break 
   
1:55-2:55Theme: TheoryChair: Yiqing Xu
 Sadegh ShiraniCausal Message-passing: A General Method for Experimentation Under Network Interference
 Asher SpectorModel-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects
 Hui LanCausal Q-Aggregation for CATE Model Selection
 Joy He-YueyaResource-efficient Pure Exploration for Contextual Bandits
   
2:55-3:00Closing 
   
3:00-5:00Poster Session and Reception