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Gravity Spy research paper wins prestigious Spanish data science award

Our interdisciplinary Citizen Science work is making international waves.

On July 3, 2023, the BBVA Foundation’s Statistics and Operations Research Society awarded Northwestern researchers “Best Applied Contribution in Statistics” for their paper “Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO“.

The Banco Bilbao Vizcaya Argentaria Foundation’s (FBBVA) distinction was designed to advance the goals of Spanish researchers working in Statistics and Operations Research and, by recognizing excellence in these two disciplines to promote their transmission to society at large. The FBBVA-SEIO award is one of the most prestigious recognitions in Spain in the field of Statistics and Operations Research, and includes a 6,000 EUR award. Awardees included CIERA member Dr. Aggelos K. Katsaggelos (Electrical and Computer Engineering), Northwestern’s Dr. Scott Coughlin (former CIERA graduate student and Computational Specialist, now Senior Computational Scientist at NUIT) as well as Dr. Pablo Morales-Álvarez (Statistic and Operations, University of Granada), Dr. Pablo Ruiz (Data Scientist, Chartboost and Northwestern Postdoctoral Alum) and Dr. Rafael Molina (Computer Science and Artificial Intelligence, University of Granada).

“In this paper, described by the committee as ‘highly innovative’, we apply a statistical method to the detection of gravitational waves, perturbations in the space-time fabric caused by violent events like the fusion of two black holes,” says Dr. Katsaggelos. “The systematic detection of such phenomena – predicted by Einstein’s Theory of Relativity in 1915 and observed experimentally for the first time in 2015 –, is a costly process, since detector technology is highly sensitive to different sources of noise. In this research we used a statistical technique known as Gaussian Processes to automatically classify the different noise signals obtained by the detector. Another important feature of the project is that it is partly a product of citizen science, with over 30,000 volunteers providing more than seven million labels for almost 1.5 million signals. This labeling technique using non-experts, and the huge amount of data available, posed significant methodological challenges.”

Gravity Spy is a multi-disciplinary project bringing together astrophysicists, machine learning experts, social scientists, and volunteers from the public. The project aims to increase the sensitivity of gravitational-wave detectors, refine human-computer interaction methods, and increase public engagement in science. Gravity Spy 2.0, an extension to the original Gravity Spy project that enables the public to investigate complex interactions between gravitational-wave detectors and environmental monitors, will be launching soon.

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