The Princeton Laboratory for Artificial Intelligence (AI Lab) is pleased to announce a call for proposals for the AI Seed Grant Program. Grants will be distributed in four…

“FlyWire,” a Princeton-led team of scientists and citizen scientists, has now made a massive step toward understanding the human brain by building a neuron-by-neuron and synapse-by-synapse roadmap — scientifically speaking, a “connectome” — through the brain of an adult fruit fly (Drosophila melanogaster). 

“As of right now, it is unclear how to provide assurances that your model can’t be used for some harmful purpose, even if people can remove all your safeguards, and whether that’s even a tractable problem,” said Peter Henderson, an assistant professor at Princeton University with appointments in the Department of Computer Science, the School of Public and International Affairs and the Center for Information Technology Policy. “We get into this gap between what’s currently technically possible and what policymakers might want.”

As a part of a broad set of investments around artificial intelligence, Princeton University has launched AI for Accelerating Invention, an initiative to achieve faster breakthroughs across engineering disciplines, including biomedicine, robotics and nuclear fusion.

Owen Travis, ’24, began playing Go in middle school after a friend took him to the Evanston Go Club in Illinois. In 2016, the AlphaGo computer program beat top player Lee Sedol at the strategy board game and Travis, who remembers reading about the defeat, found himself interested in the intersection of Go and machine learning. 

Robotic arms are already common in factories, where they paint or weld parts, pick items from conveyor belts, and stack products. But how can we move robotic arms out of controlled settings and into our everyday lives, where they can perform common tasks like dishwashing or grocery shopping? Gan Luyang ‘26, is spending her summer tackling this question and gaining research experience in the Princeton Vision & Learning Lab. 

By the time she arrived at Princeton to start her MPA, Kim Kreiss was already prepared to begin an SML certificate to compliment her degree. “Before I got to campus, the Center for Statistics and Machine Learning was definitely on my radar,” said Kreiss.

Michael Skinnider, an assistant professor in the Princeton Branch of the Ludwig Institute for Cancer Research and the Lewis-Sigler Institute for Integrative Genomics and participating faculty at the Center for Statistics and Machine Learning Princeton, received the 2023 NOMIS & Science Young Explorer Award grand prize at a ceremony at…

In 2018, Olga Russakovsky, an associate professor of computer science, received an Innovation Research Grant from the School of Engineering and Applied Science. With her colleague, computer science professor Arvind Narayanan, the funding allowed Russakovsky and her team to develop an open-source tool that uncovers biases in visual data sets, as…

Jamie Chiu, a second-year Ph.D. student in psychology and certificate student in the Center for Statistics and Machine Learning, was recognized for her work as a preceptor in “From Animal Learning to Changing People’s Minds,” taught by Yael Niv, professor of psychology and neuroscience.