The focus of the workshop is to introduce core concepts of causal inference to a broad engineering audience and how it can help lead to better modeling, algorithms, architecture design, and performance analysis. Thus, enabling better decision-making in core engineering systems. The audience will be a mix of researchers across engineering disciplines.
As part of the workshop, we will be accepting short papers that are broadly at the intersection of causal inference, engineering, and operations research. This will be non-archival and accepted papers will be presented as posters. Papers should be submitted via the following google form. Authors are asked to submit extended abstracts that are at most 4-pages in length. Please use the standard PER format (http://www.sigmetrics.org/sig-alternate-per.cls). There will also be a poster session for accepted papers.
If there are any questions, please contact Anish Agarwal (first_name.last_name@gmail.com).
8:30am - 9:15am: Why do Engineers Need Causal Inference?
Devavrat Shah
9:15am - 10:00am: Break
10:00am - 11:30am: Panel Data, Synthetic Controls, Matrix/Tensor Completion.
Alberto Abadie
Anish Agarwal
11:30am - 1pm: Lunch + Student Posters
1pm - 2:30pm: Sequential Decision-Making with Observational Data and/or De-biased ML.
Vasilis Syrkgakis
Raaz Dwivedi
2:30pm - 3pm Break
3pm - 4:30pm: Causal Inference on Networks & Applications to Modern Platforms.
Christina Lee Yu
Hannah Li
4:30pm - 5:00pm: Student Posters + Closing Remarks
Alberto Abadie
(MIT)
Anish Agarwal
(Columbia)
Raaz Dwivedi
(Cornell)
Hannah Li
(Columbia)
Devavrat Shah
(MIT)
Vasilis Syrgkanis
(Stanford)
Christina Lee Yu
(Cornell)
Paper submission: May 10th, 2023
Author notification: May 15th, 2023
Workshop date: Jun 19, 2023 (full day)