Associated Faculty
Ryan Adams
Professor
Sanjeev Arora
Charles C. Fitzmorris Professor
Danqi Chen
Assistant Professor
Tri Dao
Assistant Professor
Jia Deng
Associate Professor
Adji Bousso Dieng
Assistant Professor
Benjamin Eysenbach
Assistant Professor
Tom Griffiths
Henry R. Luce Professor of Information Technology, Consciousness and Culture
Elad Hazan
Professor
Peter Henderson
Assistant Professor
Manoel Horta Ribeiro
Assistant Professor
Aleksandra Korolova
Assistant Professor
Lydia Liu
Assistant Professor
Olga Russakovsky
Associate Professor
Sebastian Seung
Professor of Computer Science and Princeton Neurosciences Institute
Ellen Zhong
Assistant Professor
Associated Grad Students
Gianluca Bencomo
Atharva Kamat
Zhou Lu
Elizabeth Mieczkowski
Abhishek Panigrahi
Ahmed Shuaibi
Kathryn Wantlin
Tedi Zadouri
Cindy Zhang
Related News
January 22, 2025
Adji Bousso Dieng recognized by The Africa Report
Adji Bousso Dieng, expert in artificial intelligence, has been recognized by The Africa Report magazine as one of 10 African Scholars to Watch in 2025.
December 2, 2024
More checks make AI fairer
Currently, AI engineers evaluate fairness with a single leaderboard number, but research from Princeton Engineering shows that reducing fairness to a single metric could lead to societal harm.
July 31, 2024
Lydia Liu, an expert on the social impacts of machine learning, has joined the faculty
Lydia Liu, an expert on the social impacts of machine learning, joined the computer science faculty as an assistant professor in January 2024.
June 6, 2024
Ben Eysenbach, an expert in reinforcement learning, joins the faculty
Ben Eysenbach, an expert in reinforcement learning, has joined the computer science faculty as an assistant professor.
May 1, 2024
Science has an AI problem. This group says they can fix it.
A growing body of evidence has revealed deep flaws in how machine learning is used in science, a problem that has swept through dozens of fields and implicated thousands of erroneous papers.
January 29, 2024
Researchers harness large language models to accelerate materials discovery
Princeton researchers have created an artificial intelligence tool to predict the behavior of crystalline materials, a key step in advancing technologies like batteries and semiconductors.
