Thoughtworks to develop software for MeerKAT Radio Telescope
Thoughtworks, a software and digital transformation consultancy, today announced a 2-year partnership with Inter-University Centre for Astronomy and Astrophysics (IUCAA) to design, develop, test and deploy automated data processing software for the MeerKAT radio telescope, a Square Kilometer Array precursor, that will break new ground in astronomical observations and redefine our understanding of space. Thoughtworks will archive, process, analyze and distribute data and/or data products for MeerKAT Absorption Line Survey (MALS) through the Automated Radio Telescope Data Processing Software pipeline.
Today's announcement is a testament to Thoughtworks' expertise in data-intensive scientific discovery and the Engineering for Research (E4R) practice that secured the contract. Previously, Thoughtworks designed and delivered software for the Thirty Meter Telescope, an observatory that will produce images ten times sharper than the Hubble Space Telescope.
The MeerKAT project is led by Dr. Neeraj Gupta and Raghunathan Srianand of IUCAA, India. Dr. Neeraj has this to say on the transformative expectation of the project, "The work to be completed by Thoughtworks will allow us to use cutting-edge and innovative solutions required to tackle the big data challenge, posed by MALS and, improve our understanding of how galaxies form and evolve."
"Engineering excellence is the backbone that powers technology," says Sameer Soman, Managing Director, Thoughtworks India. "Our work on the MeerKat project enables the continued evolution of discovery and design when it comes to managing and processing incredibly large data sets. Also, as always Thoughtworks will look forward to enterprise level applications of our learnings from this futuristic project."
About Engineering for Research, E4R
E4R is Thoughtworks initiative to design and develop software tools for scientific discovery, as a part of the larger computational science community. The practice is focused on solving next-generation computational challenges across various scientific disciplines such as astronomy and biology.