Center for Statistics and Machine Learning

Featured 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.

Next Event

Spectral Transformers
Tue, Feb 4, 2025, 12:00 pm

Lunch is available beginning at 12 PM

Speaker to begin promptly at 12:30 PM

Abstract: We'll discuss a new technique for sequence modeling for prediction tasks with long range dependencies and fast inference/generation. At the heart of the method is a new formulation for state space models (SSMs) based on…

Open Positions

Open Rank Faculty Positions in Interdisciplinary Data Science
Sept. 18, 2024

As part of a major new initiative in interdisciplinary data science, Princeton University is searching for tenured and tenure-track faculty members across all science, engineering, social science, and humanities areas. This initiative will involve multiple faculty hires over the next several years. We are particularly interested in applicants…


 

Latest News

Adji Bousso Dieng: evaluating diversity in generative AI

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

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

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

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…