• Zwicky Transient Facility Achieves First Light

    Marks the beginning of commissioning of the next generation time domain survey.

  • DIRAC on FiRe

    DIRAC Director Andy Connolly discusses with Mark Anderson how the scale of the imaging data that will come from a new generation of telescopes will require different analysis methodologies.

  • ADAM Hack Days 2017

    DIRAC hosted the first B612/Asteroid Institute ADAM (“Asteroid Decision/Analysis Machine”) HackDays.

  • LSSTC Data Science Fellowship Program

    The 4th session of the LSSTC Data Science Fellowship Program took place at the University of Washington in September 2017.

Mission

From fundamental research on the most energetic events in the universe to the search for asteroids that may one day impact the Earth, the science of the next decade will be driven by data. Our ability to make scientific breakthroughs will…

Research

DIRAC brings together researchers from Astrophysics, Computer Science & Engineering, Statistics, and other key disciplines to develop algorithms and infrastructure to process, analyze, and understand the science and questions arising from major astronomical imaging telescopes (e.g. LSST, MWA, SKA, Advanced…

People

DIRAC is creating an environment where scientists can harness interdisciplinary expertise to solve some of the most difficult questions facing Astronomy today. It  provides an interaction space between Astrophysics, Computer Science, Statistics, and other disciplines. It is a place where ideas…

Talks

2017-11-14 Lunch Seminar: John Swinbank

John Swinbank will review the design and scientific goals of LSST, provide an update on the current status of construction, explore some of the algorithmic and data processing challenges that the LSST Data Management team faces, and describe the key role that members of the Department of Astronomy here at UW are playing in making it all possible.

2017-11-01 LSST/DM Brown Bag: Stephen Portillo

Stephen Portillo will be discussing “Improved Source Detection in Crowded Fields using Probabilistic Cataloging”, based on his work on probabilisitic cataloging described in arXiv:1703.01303. 

Visitors: Jorge Vergara

Jorge is a machine learning expert who works on feature selection, identifying which features provide the most information in a data set. Visiting July 26th to October 26th, 2017.

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Visitors: Tamas Budavari

July 24-28th 2017: Tamas Budavari is Assistant Professor in the Department of Applied Mathematics & Statistics in the Whiting School of Engineering at the Johns Hopkins University, where he focuses on computational and statistical challenges of big data.

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Visitors: Francisco Förster

Francisco Förster is the PI of the HITS program (a time domain survey using the Blanco 4m at CTIO that has been used for supernova, asteroid, and variable star detection). July 16th to 21st, 2017.

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