What would happen if hundreds of social scientists and data scientists worked together on a scientific challenge to improve the lives of disadvantaged children in the United States?
Princeton University has approved the creation of a new certificate program for graduate students through its Center for Statistics and Machine Learning, with enrollment beginning in January 2018.
Companies and academic institutions of New Jersey have a unique opportunity to solve health care problems and grow new businesses at the intersection of biotechnology and data science, a panel of leaders from industry and academia concluded at a conference convened by Princeton University on Oct. 25.
Three Princeton University projects are among the 121 selected by the National Institutes of Health to receive an overall $219 million in funds related to the federal Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative.
Barbara Engelhardt, an assistant professor of computer science at Princeton and SML Certificate Executive Committee Member, is a principal investigator with the GTEx Consortium, an international group of researchers studying the diversity of genetic roles in maintaining human tissues.
Olga Troyanskaya and her team have developed techniques to comb large collections of genomic and other data to make fundamental discoveries and identify new therapeutic targets. These “big data” methods can be applied to numerous disorders for which people can have genetic susceptibilities, from cancer and chronic kidney disease to autism and...
Cathy Chen remembers wondering, as a freshman, how her interests in applied math, algorithms, and programming would ever come together. “I’d say the ‘a-ha!’ moments came during my sophomore year,” she recalls. “I took a cognitive neuroscience class taught by Professor...
Five Princeton University professors have been selected to receive 2017 Simons Investigators awards, which are presented by the New York-based Simons Foundation to outstanding scientists nationwide engaged in...
CSML welcomes its new director, Professor Peter J. Ramadge the Gordon Y.S. Wu Professor of Engineering and Professor of Electrical Engineering. His research interests range from theoretical aspects of machine learning and data analysis to the applications of machine learning in domains such as neuroscience, robotics, and signal processing.