In a new video, scholars from across the Faculty of Arts and Sciences explain how the recent explosion of data in our world presents both challenges and opportunities in their quest to better understand human behavior.

Yale is part of a new, multi-institution research center focused on understanding and controlling turbulence — one of the oldest unsolved problems in physics. TEMPEST, which will be based at Michigan State University, brings together physicists, mathematicians, engineers, and AI researchers — including Yale’s Anna Gilbert, the John C. Malone Professor of Statistics and Data Science.

This new video highlights three scholars — Cosmochemist Damanveer Grewal, Egyptologist Victoria Almansa-Villatoro, and Data Scientist Johan Ugander — who joined Yale’s Faculty of Arts and Sciences in the Fall of 2025.

Lu, Assistant Professor of Statistics and Data Science, was named to the list for his work "pioneer[ing] a paradigm shift in Scientific Machine Learning (SciML)."

Two multidisciplinary research teams composed of FAS faculty are seeking to understand why AI systems become misinformed or misaligned with users’ intentions and to develop ways to make them safer, more reliable, and more accountable.

“External validity isn’t just a statistical issue — it’s a question that runs through how we design studies, interpret results, and make decisions in the real world,” said Melody Huang, Assistant Professor of Political Science and Statistics & Data Science and faculty fellow at ISPS. “This is one of the central challenges of modern science.”

In a Q&A, Yuejie Chi, Charles C. and Dorathea S. Dilley Professor of Statistics and Data Science, discusses her ongoing research into making AI more efficient.

Daniel Spielman, Sterling Professor of Computer Science and Professor of Statistics and Data Science and of Mathematics, was featured in Scientific American as a leading academic calling for AI companies to be more transparent about claims that models can do pure mathematics.

Zongming Ma, Professor of Statistics and Data Science, worked together with colleagues in Biomedical Engineering and Pathology to develop a new technology that addresses one of the most persistent challenges in spatial biology: determining how tissue sections differ from each other.

With state-of-the-art research facilities and collaborative spaces, Yale’s Wu Tsai Institute is on a mission to understand human cognition by bridging academic disciplines.