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Experimentation and Causal Inference in the Tech Sector

Event Details:

Monday, June 5, 2023
9:00am - 5:00pm PDT

Location

Vidalakis Dining Hall, Schwab Residential Center, 680 Jane Stanford Way, Stanford, CA 94305

This event is open to:

Alumni
Faculty/Staff
General Public
SDS Industry Affiliate Members
Postdocs
Students

This one-day event provides a unique opportunity to engage with top experts in experimentation and causal inference from both academia and industry. 

The goal of this workshop is to bring together researchers, practitioners, and industry professionals to discuss cutting-edge methodologies and their real-world applications. We are thrilled to share that we have an excellent lineup of speakers who are leading figures in the tech industry and academia. This workshop is an excellent opportunity for networking, learning, and discussing the latest trends in causal inference in the tech sector. 

Agenda:  
9:30-10:00amRegistration
10:00 - 10.15amOpening: Guido Imbens
10.15-11.45amSession 1: Chaired by Emma Brunskill
 Martin Tingley (Netflix), Experimentation Platform at Netflix: Building Useful Inference
 Min Liu (LinkedIn), Online Experimentation at LinkedIn
 Art Owen (Stanford), Multibrand Geographic Experiments (with Tristan Launay)
11:45-12:00pmBreak
12:00 - 12:45pmPoster Session
12:45-1:30pmLunch
1:30-3:00pmSession 2: Chaired by Stefan Wager
 Emily Glassberg-Sands (Stripe), Policy Optimization at Stripe (with Kyle Carlson)
 Alex Chin (Lyft), Policy Evaluation and Optimization with Multi-agent RL Environments at Lyft
 Bin Yu (UC Berkeley), Using Predictability and Stability to Reduce Design Space for Causality
3:00-3:15pmBreak
3:15-4:45pmSession 3: Chaired by Ramesh Johari
 Ali Rauh (Airbnb), Experimentation Challenges at Airbnb
 Ramon Huerta (Amazon), Mitigating the impact of confounders in Machine Learning
 Vasilis Syrgkanis (Stanford), Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
4:45-6:00pmReception

SC^2 focuses on providing an interdisciplinary community for scholars interested in causality and causal inference. We aim to be a nexus where participants can learn about methods for causal inference in other disciplines and find opportunities to work together on such questions.

This event is sponsored by the Stanford Causal Science Center (SC²) and Stanford Data Science. 

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