Newsroom
Causal Inference
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Dissertation Defense: Anay Mehrotra, “Learning Theory in the Wild: Foundations of Missing Data and Language Generation”
Abstract: What can be learned from data? This fundamental question in machine learning takes on new complexity in modern pipelines where classical assumptions fail—both […]
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S&DS Seminar: Adam Block (Columbia), “Scaling Inference-Time Compute: From Self-Improvement to Pessimism”
Abstract: Language models increasingly rely on scaling inference-time computation to achieve state-of-the-art performance on a growing number of reasoning tasks. A popular paradigm for […]
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FDS Colloquium: Anay Mehrotra (Yale), “What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness”
Talk summary: Sometimes, like when studying the effects of smoking, it is impossible to run a randomized control trial and we must rely on […]
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Yale FDS Researchers Win Best Paper at COLT 2025 for Foundational Work in Causal Inference
Colt 2025 Best Paper Award went to an all-Yale team. Pictured left to right: Anay Mehrotra, Alkis Kalavasis (FDS Postdoc), Manolis Zampetakis, and Katerina Mamali. Not pictured: Yang Cai.
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FDS Colloquium: Kristina Gligoric (Stanford), “Supporting policies and interventions to promote healthy and sustainable habits”
Abstract: Data science tools create new opportunities to assist policy-makers. For example, enabling healthy and sustainable diets is key to addressing preventable diseases and […]
