Princeton University unveiled an AI research collaboration with Google late last year. (U.S. 1, January 30, 2019.) Now the school has announced another major effort to put AI to work in a variety of uses across the university.
Princeton University researchers will push the limits of data science by leveraging artificial intelligence and machine learning across the research spectrum in an interdisciplinary pilot project using a grant from Schmidt Futures, a venture fund started by 1976 Princeton alumnus Eric Schmidt, the former chairman of Google and its parent company, Alphabet.
“The Schmidt DataX Fund will accelerate Princeton researchers’ use of artificial intelligence and machine learning to explore questions at the frontiers of human knowledge. These techniques are transforming the scholarly landscape, and I expect their importance will grow rapidly in the years ahead,” Princeton University President Christopher L. Eisgruber said.
“This is a time when visionary leaders who apply new computing technologies and work together across departments and fields can make a huge difference,” said Eric Schmidt. “This new gift aims to build upon Princeton’s long record of research excellence by accelerating the application of the most modern computing, machine learning and artificial intelligence techniques to problems of greatest social and intellectual importance.”
The funds will support a range of data science initiatives led by the Center for Statistics and Machine Learning, including: development of graduate-level courses in data science and machine learning; creation of mini-courses and workshops to train researchers in the latest software tools, cloud platforms and public data sets; and innovation funds to jump-start new research projects through funding for postdoctoral fellows, graduate or undergraduate students, and access to data sets and cloud resources.
The funds will also support six Schmidt Data Scientists who will create and improve data-analysis software to operate at large scale.
Some scientists believe the power of catalytic chemical reactions will be the key technological driver for solutions to many problems of increasing social concern, including the development of alternative energy technologies, environmental remediation strategies, access to non-fossil-fuel-based and inexpensive pharmaceuticals and antibiotics, sustainable agriculture, and renewable soft materials. Working with Princeton’s chemists and other researchers, Schmidt Data Scientists will leverage machine learning in the discovery, optimization and application of catalytic reactions. They will build tools to make the enormous volumes of unpublished data more available and useful, and they will create user-friendly software to speed the adoption of data science to increase the pace of research in this field.
Genome-reading technologies have revolutionized the biomedical sciences, generating enormous quantities of genetic data — far too much to be easily useful. Schmidt Data Scientists will take steps to manage these data sets and navigate the protections that govern human data, providing an efficient, shared infrastructure to accelerate research in biomedical data science.
The biomedical science initiative is spearheaded by the Department of Computer Science, with connections to the Lewis-Sigler Institute for Integrative Genomics, Princeton Neuroscience Institute and several engineering departments. Faculty members who apply machine learning to biomedicine include Ben Raphael, a professor of computer science who has used the approach to identify which pancreatic cancer cells could respond to targeted gene therapies, and Olga Troyanskaya, a professor of computer science and the Lewis-Sigler Institute for Integrative Genomics who developed software to study he genetics of worms.
Princeton research on information technology policy, driven by CITP and involving faculty from across the University, covers a broad range of data science topics. Areas of focus include security and privacy, bias and fairness, manipulation of data for social or political aims, and long-term workforce implications of advances in artificial intelligence. CITP is led by Ed Felten, professor of computer science and public affairs, and it has 17 affiliated faculty members.
Princeton University, 1 Nassau Hall, Princeton 08544. 609-258-3000. Christopher Eisgruber, president. www.princeton.edu.