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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.
In the 19th century, printing technology changed the way readers experienced texts. Today, students and researchers are using digital technology to access historical literary texts in new ways and finding surprising echoes of the past in their own lives.
During a downtime period in which the Large Hadron Collider is not producing data, Princeton and CERN physicists work on the installation of the pixel luminosity telescope of the CMS experiment. Shown from left: David Stickland, Princeton; and Rob Loos and Anne Dabrowski, CERN.
© 2015-2018 CERN
With the goal of creating next-generation computing power to support high-energy physics research, the National Science Foundation (NSF) announced today that Princeton University will lead a new NSF-funded coalition of 17 research universities to be called the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP).
Deep Learning Leader William Tang
(Photo by Elle Starkman/Office of Communications)
To capture and control the process of fusion that powers the sun and stars in facilities on Earth called tokamaks, scientists must confront disruptions that can halt the reactions and damage the doughnut-shaped devices. Now an artificial intelligence system under development at the U.S.
At podium, Alfredo Canziani, post-doc at NYU’s Center for Data Science, speaks to CoDaS-HEP attendees about machine learning. Photo by Florevel Fusin-Wischusen, Princeton Institute for Computational Science and Engineering
As thunderstorms rumbled across the region, fifty-six high energy physics graduate students and twelve presenters from across the United States, as well as from India, Pakistan, France, and Norway, gathered at the Princeton Center for Theoretical Science (PCTS) to attend the Computational and Data S
The TIGER HPC computing cluster in the High Performance Computing Research Center, Princeton’s 47,000-square-foot data center.
Four members of the PICSciE-affiliated research team that designed the experiments and developed the FRRN code: Chief architect of the FRNN is Julian Kates-Harbeck (inset photo), a graduate student at Harvard University and a DOE Office of Science Computational Science Graduate Fellow; Eliot Feibush (standing, center), a computational scientist and experienced data analyst at PPPL, Dr. Alexey Svyatkovskiy (seated), a deep learning/AI expert and collaborator, and Dr. William Tang, lead researcher. Photo credit: Elle Starkman, Princeton Plasma Physics Laboratory
In scientific research, results don’t just have to be good—they have to be reproducible. Members of the PICSciE-affiliated research team are achieving both, as they apply a deep-learning AI approach to the problem of disruption forecasting in tokamak fusion plasmas.
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Education and Training
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Enabling Princeton's Research Community
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Systems and Services
Training
Introduction to QGIS (offered twice a semester)
Wed, Nov 14, 2018, 1:30 pm to 3:00 pm
Location:
225 Lewis Library Electronic Classroom
Princeton University Python Community Kickoff Event
Wed, Nov 14, 2018, 4:00 pm to 5:30 pm
Location:
347 Lewis Library, Vis Lab
Help Sessions
Weekly Help Sessions in Visualization & Programming
Thu, Nov 15, 2018, 2:00 pm to 3:00 pm
Location:
347 Lewis Science Library
Weekly Help Sessions
Other Events
Princeton University Python Community Kickoff Event
Wed, Nov 14, 2018, 4:00 pm to 5:30 pm
Location:
347 Lewis Library, Vis Lab
Image Analysis using Python
Tue, Dec 4, 2018, 4:00 pm to 5:00 pm
Location:
347 Lewis Library, Vis Lab
Research News
Wednesday, Aug 17, 2016
The amount of data encompassed by the global climate in its entirety, from its winds and temperature conditions to shifting formations of cloud,...
Wednesday, Aug 17, 2016
Turbulent combustion is just that. Jet engines and high-power furnaces produce a great amount of energy, along with its byproduct: emissions in...
Wednesday, Aug 17, 2016
Energy is central to civilization as we know it. It’s also environmentally untenable in its current state. This is an issue Professor Emily Carter...
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