Princeton University held its first computing bootcamp for graduate students and postdocs on Oct. 29 to Nov. 1, four days of short introductory-level lectures and hands-on exercises on a variety of topics, tools and techniques necessary for modern computational research careers. Some 80 graduate students and postdocs from 21 departments signed...
On Oct. 16-17, some 60 Princeton graduate students and postdocs — along with a handful of undergraduates — explored the most widely used deep learning techniques for computer vision tasks and delved into using new parallel computing programs to dramatically speed up applications.
Joseph Abbate, 22, Class of 2018:
How should society decide who gets a liver transplant? Should there be marketplaces for data in the near future and how should these markets be run? If a driverless car kills someone, who is at fault? And how can randomness help optimize algorithms used in machine learning?
Lydia Liu, 24, Class of 2017:
Studies: Lydia Liu earned a bachelor’s degree in Operations Research and Financial Engineering at Princeton University, as well as certificates from the Center for Statistics and Machine Learning, Program in Applied and Computational Mathematics, and the Department of Computer Science.
Cathy Chen, 22, Class of 2018:
Chen earned her bachelor’s degree in computer science and earned three certificates: the Center for Statistics and Machine Learning’s Certificate in Statistics and Machine Learning, and certificates in applied and computational mathematics, and...
For three weeks this summer, high school students packed the conference rooms of Princeton’s Computer Science building, honing programming skills while taking on challenges in artificial intelligence — from sharpening computer vision for self-driving cars to identifying fake or misleading online news.
Data scientist Michael Guerzhoy will join Princeton University’s Center for Statistics and Machine Learning as a lecturer, effective September 1.
When Ryan P. Adams looks at the ever evolving landscape of machine learning, statistics, and data science, the Princeton University computer science professor gets excited about how tools from the field can potentially provide unconventional, insightful solutions for complex problems, from developing new medications to creating new sources of...