BigDataX: From theory to practice in Big Data computing at eXtreme scales
This award aims to establish a Research Experiences for Undergraduates (REU) site named BigDataX, which will focus on undergraduate research in both theory and practice of big data computing at extreme scales.
The primary objective of this award is to promote a data-centric view of scientific and technical computing, at the intersection of distributed systems theory and practice. This award aims to have four mentors at the Illinois Institute of Technology and University of Chicago, with a variety of complementing expertise from theory to programming languages to distributed systems. This work includes a comprehensive educational plan integrating eight undergraduate students with senior PhD students with incremental manageable goals, aimed at allowing undergraduate students to achieve publishable results within the ten week summer program. The group will maintain a public social network presence through a LinkedIn group at https://www.linkedin.com/groups/8301753.
Below is BigDataX REU 2015 Site along with the MEDIX REU 2015 Site visiting Argonne National Laboratory in July 2015.
Below is BigDataX REU 2016 Site along with the MEDIX REU 2016 Site visiting Argonne National Laboratory in June 2016.
Below are REU and DataSys students at the IEEE/ACM Supercomputing/SC 2016 conference in Salt Lake City Utah in November 2016.
Below is William Agnew (REU 2016 student) receiving the ACM Undergraduate Student Research Award at the IEEE/ACM SC 2016 conference.
Award: $288K, 03/2015 - 02/2018; for more details, see the NSF description
Funding Period: 2015 - 2018
- Summer 2015 (06-15-2015 to 08-21-2015)Summer 2016 (05-23-2016 to 07-29-2016)
- Summer 2017 (05-22-2017 to 07-28-2017)
- IIT: Illinois Institute of Technology
- UChicago: University of Chicago
- Ioan Raicu (IIT)
- Gruia Calinescu (IIT)
- Kyle Hale (IIT)
- Mike Wilde (UChicago)
- Justin Wozniak (UChicago)
- Kyle Chard (UChicago)
- Matthew Bauer (IIT)