Princeton is a key partner in a New Jersey state AI hub, and the University has launched initiatives on precision health, language and intelligence, and accelerated innovation, bringing together experts to tackle emerging challenges and opportunities in AI. At the same time, the Department of Computer Science is meeting the students' booming interest in AI through courses that delve into the underlying technologies as well as their societal impacts.
New Jersey AI hub
New Jersey Gov. Phil Murphy and University President Christopher L. Eisgruber unveiled a plan last December to create an artificial intelligence innovation hub for the state in collaboration with the New Jersey Economic Development Authority.
The initiative will bring together AI researchers, industry leaders, startup companies, and other collaborators to advance research and development. Priorities include advancing the use of ethical AI and promoting workforce development in collaboration with other New Jersey universities, community colleges, and vocational schools.
“We have the potential to pioneer technologies that could unlock new cures for debilitating diseases, or new solutions for combating climate change, or new methods for educating our students so that every child can receive the personalized attention they deserve and need to reach their full potential,” Murphy said. “With AI, we have a chance to confront — and perhaps overcome — some of the greatest challenges facing our world.”
Princeton Precision Health
Princeton researchers are working to make health care more precise and effective. But they’re not working with patients, they’re working with data.
Created in 2022, Princeton Precision Health is an interdisciplinary initiative for AI and data-driven approaches to health care challenges. The initiative uses advanced AI methods on large, complex data sets to make health care policy and delivery more precise, effective, and unbiased.
Led by Olga Troyanskaya, a professor of computer science and the Lewis-Sigler Institute for Integrative Genomics, PPH focuses on four areas: kidney disease and diabetes; the immune system and inflammation; neurodevelopment, neurodegeneration, and mental health; and technology and mental health. The organization has hosted symposia, lectures, and discussion groups, and provided research grants to faculty. The initiative aims to convene experts from many fields — including computer science, biology, environmental science, social science, economics, policy, psychology, ethics, and medicine — to collaborate on interdisciplinary AI-based approaches to improve health outcomes.
“We can address very hard health challenges involving researchers across domains, from computational biology to epidemiology to social science and ethics,” Troyanskaya said.
Language and Intelligence initiative
The Princeton Language and Intelligence initiative is deploying the University’s resources and academic strengths to enhance understanding of artificial intelligence; examine its safety, policy, and ethical implications; and enable its use across disciplines.
Announced in September 2023, the initiative is led by Sanjeev Arora, Princeton’s Charles C. Fitzmorris Professor in Computer Science, who has conducted research at the intersection of language and AI for many years. The initiative will support a group of postdoctoral research fellows, research scientists, and engineers exploring key questions about the technology. It also has enabled the purchase a large computational cluster to give Princeton researchers access to the resources needed to work with large language models.
“AI is in danger of developing primarily inside private labs, with little opportunity for the rest of the world to know how it works or be assured that it is responsibly deployed with full safeguards,” said Jennifer Rexford, Princeton University provost and Gordon Y.S. Wu Professor in Engineering. “We are committed to keeping AI expertise and know-how in the public sphere. We are eager to work with institutional partners and companies who share our commitment to open research. Initiatives such as PLI can democratize AI knowledge, enhance transparency and accountability, and help ensure that benefits of AI accrue to all of humanity.”
This article was adapted from a previously published story.
AI Accelerated Innovation
Reflecting rapid advances in artificial intelligence and machine learning, the School of Engineering and Applied Science’s new AI Initiative will help accelerate innovation across engineering disciplines.
Led by Mengdi Wang, associate professor of electrical and computer engineering and the Center for Statistics and Machine Learning, and Ryan Adams, professor of computer science, the initiative, called AI Accelerated Innovation, aims to develop techniques to apply artificial intelligence to each step of technological innovation: design, simulation, fabrication, and control. The initiative builds on much work already underway at Princeton, such as using AI to design new energy technologies, medicines, computer chips, and construction techniques.
Such uses do not replace human intelligence, but extend it, Adams said. “How can we build systems that can do things for us that we cannot do for ourselves?”
The initiative will support new research through seed grants, postdoctoral positions, and computing resources, while providing internships, seminars, and other professional development.
The initiative will take advantage of Princeton’s “tight-knit community of exceptionally high-quality researchers,” the organizers said. “The goal is to create a collaborative, welcoming, resource-rich environment in which new research partner-ships across disciplines can emerge and change the way engineering is done.”
Students delve into AI and its impacts
With nearly half of computer science undergraduates studying artificial intelligence, demand for AI-related courses, independent work, and senior theses is booming. Out of 10 faculty members hired since 2022, half have expertise that adds to longstanding department strengths in computer vision, machine learning, natural language processing, and the ethical implications of AI. Teaching students to think about the social impact of AI, department chair Szymon Rusinkiewicz said, is as critical as teaching them how to build the technology. “Our goal is to make sure the computer science department at Princeton is well positioned to do both,” he said.
