Topcoder members participating in the data science challenge conducted by NASA developed algorithms that detected two sungrazing comets

Topcoder, a Wipro company, announced today that the Comet Detection Marathon Match Challenge, conducted on behalf of NASA SOHO/ESA to develop artificial intelligence and machine learning (AI/ML) algorithms capable of detecting comets that reflect minimal light, resulted in the finding of two previously undetected comets. The winning algorithms will be utilized by NASA’s Solar and Heliospheric Observatory (SOHO) satellite to improve comet detection to find previously overlooked C2 comets and the discovery of non-group comets.

Nearly 600 Topcoder members worldwide, including professionals and freelancers, participated in the competition by developing AI/ML algorithms to enhance the SOHO satellite’s imagery and data capabilities. Seven entries earned a share of the $29,000 in cash prizes NASA allocated to the competition, with the winner taking home $9,000. In addition to the prize money, the winning participants will earn discovery credit for the comets found using their developed algorithms.

“Topcoder is the world’s top open talent platform for developers, designers, and data scientists,” said Doug Hanson, CEO, Topcoder. “We are proud to work with NASA to accelerate the development of new algorithms to make comet discovery easier. We believe that the power of competition and open innovation can solve any problem on earth or beyond, and we are excited to see the solutions developed by Topcoder members being used in the next frontier of exploration.”

SOHO is a cooperative international mission between the European Space Agency (ESA) and NASA’s Goddard Space Flight Center (GSFC). SOHO’s Large Angle and Spectrometric Coronagraph, or LASCO, is an onboard instrument that provides most of the imagery, with two coronagraph telescopes designed to block direct blinding sunlight and observe the much fainter solar corona and solar outflows. As an unintended consequence of LASCO’s sensitivity, LASCO also detects large numbers of previously unknown sungrazing comets. Since it was launched in 1995, the SOHO satellite has detected more than 4,000 new comets. NASA is optimistic that the data-enhancing algorithms developed through the Marathon Match Challenge could have utility beyond comet discovery and tracking for SOHO, and that they may be applicable to coronagraph imagery on other heliophysics observatories.

The Topcoder Marathon Match Challenge is supported by the NASA Open Source Science Initiative and is part of a broader effort to showcase the cross-disciplinary use of NASA’s science data and encourage public engagement with science data-related problems.

About Topcoder

Topcoder, a Wipro company, is a community where you can connect, learn, and earn. We are competitive in nature and nurturing at our core. We connect incredibly talented individuals across the globe with customers who have tough problems to solve. As an open talent platform, Topcoder offers competitive programming, coding competitions, freelance gigs, along with learning and up-skilling opportunities. For 20 years, Topcoder has helped organizations — including Adobe, Comcast, Google, Harvard Medical School, Land O’Lakes, Microsoft, NASA Tournament Lab, SpaceNet, T-Mobile, U.S. Dept. of Energy, Zurich Insurance, and more. For more information, visit www.topcoder.com.

About Wipro Limited

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading global information technology, consulting, and business process services company. We harness the power of cognitive computing, hyper-automation, robotics, cloud, analytics, and emerging technologies to help our clients adapt to the digital world and make them successful. A company recognized globally for its comprehensive portfolio of services, strong commitment to sustainability, and good corporate citizenship, we have over 220,000 dedicated employees serving clients across six continents. Together, we discover ideas and connect the dots to build a better and a bold new future.

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