Thursday, Apr 18, 2019

Princeton University seeks data scientists funded by the Schmidt DataX project. The fund supports six data scientists who will create and improve data-analysis software to operate at large scale, leading to faster discovery, wider impact and greater continuity.

Wednesday, Aug 21, 2019
by Sharon Adarlo

When you click on any YouTube video or buy a

Monday, Aug 12, 2019
by Sharon Adarlo

Kitty Moraes, age 21, Class of 2019

Friday, Aug 2, 2019
by Sharon Adarlo

Trung “Average” Phan, 25, doctoral student:

 Studies:

Monday, Jul 22, 2019
by Sharon Adarlo

Olga Russakovsky, Assistant Professor of Computer Science

Background:

Russakovsky is affiliated with Princeton University’s Center for Statistics and Machine Learning (CSML) and Princeton’s Center for Information Technology Policy.

Friday, Jul 19, 2019
by Molly Sharlach, Office of Engineering Communications

For social scientists addressing these questions, troves of data from social networks, news media and online transactions bring unprecedented opportunities, along with new ethical and technical challenges.

Thursday, Jun 6, 2019
by Sharon Adarlo

Dating websites are not only a great place to meet a potential mate, but are also a treasure trove of data.

Friday, May 31, 2019
by Sharon Adarlo

The “uhs” and “ums” that pepper conversational speech can seem rather unimportant. Transcribers don’t often write down these vocal interruptions when translating interviews with people or quotes for the written page. But those filler words can carry a lot of meaning, according to Marie-Fee Breyer, Princeton University senior.

Thursday, May 30, 2019
Using artificial intelligence, a Princeton University-led team has decoded the functional impact of such mutations in people with autism. The researchers believe this powerful method is generally applicable to discovering such genetic contributions to any disease.
Tuesday, May 28, 2019
by Sharon Adarlo
This past spring semester, a group of freshmen had the opportunity to explore data science in the freshman seminar course, FRS 154: Weird Data, which was co-sponsored by Princeton University’s Center for Statistics and Machine Learning (CSML) and The Center for Digital Humanities (CDH).

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