May 2026: New Research in Causal Inference & Experimental Design
**From the Editor’s Desk** This May, we reviewed 604 papers across eight domains, and what stands out is a quiet but decisive shift: the field is moving from *identifying* causal effects to *acting* on them. Across Causal Inference, Reinforcement Learning, and Sequential Decision-Making, we see a convergence on methods that not only estimate what works, but for whom, and when to stop trying.