Invited Talk at University of Copenhagen + Attending SaTML

I gave a talk “Advancing Synthetic Control for Individual-Level Causal Inference” at University of Copenhagen.

Here is an abstract of my talk:
Synthetic control is a widely used causal inference method for evaluating the effectiveness of government policies, such as new tariffs and tax increases. Traditionally, synthetic control is applied to aggregate-level datasets, but more recent studies have explored its applications to disaggregated datasets, such as individual health records and targeted marketing analyses. However, individual-level datasets exhibit different distributional properties compared to aggregate-level data. Our work reexamines the implicit assumptions of traditional synthetic control approaches and proposes theoretically grounded algorithms for synthetic control in individual-level analyses. I will discuss Cluster Synthetic Control, a synthetic control approach that incorporates a donor selection step (to be presented at AIStats 2025). I will also address privacy concerns related to individual-level data analyses and present our work on Differentially Private Synthetic Control, featured at AIStats 2023. These methods provide synthetic control approaches with provable accuracy improvements and privacy guarantees.

I will also be at SaTML conference this week, and would love to connect with anyone attending!