News

Korolova and Russakovsky receive Presidential Early Career Award for Scientists and Engineers
Jan. 22, 2025

Center for Statistics and Machine Learning participating faculty members Aleksandra Korolova and Olga Russakovsky are among the 2024 recipients of the Presidential Early Career Awards for Scientists and Engineers (PECASE). The PECASE award is the highest honor given by the U.S. government to early career scientists and engineers.

Adji Bousso Dieng: evaluating diversity in generative AI
Jan. 21, 2025
Author
Written by Allison Gasparini

The fundamental importance of diversity led Assistant Professor of Computer Science Adji Bousso Dieng to develop the Vendi Score, a metric which can be applied to evaluate and promote better diversity in generative models and datasets, among other applications. 

SML minor James Zhang named Schwarzman Scholar alongside two other Princeton seniors
Jan. 16, 2025

Princeton Class of 2025 member James Zhang has been named a Schwarzman Scholar and will attend a one-year, fully funded master’s degree program in global affairs at Tsinghua University in Beijing.

Peter Melchior: recovering more information on galaxies with machine learning
Jan. 13, 2025
Author
Written by Allison Gasparini

With the help of machine learning, Peter Melchior, assistant professor of statistical astronomy at Princeton University’s Department of Astrophysical Sciences and the Center for Statistics and Machine Learning, is working to maximize the value of the information extracted from datasets. “We’re trying to find the limit of what the data can tell us in order to tease out more information about galaxies,” said Melchior. 

New research from CSML participating faculty reveals groundwater pathways across continent
Jan. 9, 2025

Researchers from Princeton University and the University of Arizona have created a simulation that maps underground water on a continental scale. The simulation, published January 6 in Nature Water, shows that rainfall and snowmelt flows much farther underground than previously understood and that more than half the water in streams…

Symposium fosters collaboration between robotics and AI
Dec. 9, 2024
Author
Written by Allison Gasparini

Princeton University is leading the way in fostering community and collaboration among researchers in robotics and artificial intelligence. On Nov. 4, the University hosted the Princeton Symposium on Safe Deployment of Foundation Models in Robotics.

Tom Griffiths is decoding intelligence — both human and artificial — to think differently about how we think
Dec. 5, 2024

As the inaugural director of the Princeton Laboratory for Artificial Intelligence (AI Lab, for short), Tom Griffiths is helping to shape the future of AI research at Princeton. The AI Lab is an incubator that provides resources to allow Princeton researchers across disciplines to explore AI’s potential impact in their fields.…

Princeton engineers win First Prize Paper Award in the IEEE Transactions on Power Electronics (TPEL) for machine learning research
Dec. 4, 2024
Author
Written by Allison Gasparini

A team of researchers at Princeton University led by Minjie Chen, associate professor co-appointed in the Department of Electrical and Computer Engineering and the Andlinger Center for Energy and the Environment, has been awarded the First Place Prize Paper Award for 2023 in the IEEE Transactions on Power Electronics.

More checks make AI fairer
Dec. 3, 2024

In an article in the journal Patterns, Olga Russakovsky, associate professor of computer science and associate director of the Princeton AI Lab, argues for a multidimensional approach in which fairness is evaluated on several levels depending on the context of the application.

Michael Skinnider: using generative AI to accelerate discovery of small molecules
Nov. 19, 2024
Author
Written by Allison Gasparini

When the human body breaks down food or drugs or even its own tissue, it produces small molecules called metabolites. Using analytical techniques, researchers can typically detect thousands of small molecules in a sample of human tissue. While many of these molecules may be known, much of the small molecules in a given sample are unidentifiable to researchers for one reason or another. Identifying these unknowns is a question of scientific interest.