Skip to content
#data science Open access

Planet Hunters NGTS: no planet left behind in the Next Generation Transit Survey

Oct 2026 · Research Portal (Queen's University Belfast)

Abstract

In this thesis, I present the Planet Hunters NGTS citizen science project. In this project, we enlist the help of members of the public to visually vet candidates from the Next Generation Transit Survey (NGTS). The aim of this project is to detect planet candidates that were missed in initial searches of these data. By combining classifications from multiple non-expert volunteers, we are able to efficiently classify these large datasets much faster than traditional visual vetting. I present 5 new planet candidates discovered through the Planet Hunters NGTS project that were not previously detected in these data. These discoveries demonstrate that the citizen science approach can provide a complementary method to the detection of exoplanets with ground-based surveys such as NGTS and thus can improve the completeness of these surveys. I detail the identification and characterization of one of these candidates as an eclipsing binary system composed of two M-dwarfs. This system will be a valuable benchmark for testing stellar evolution models and in particular for testing the M-dwarf radius inflation problem. Finally, motivated by the recovery of this binary system in photometry from the Asteroid Terrestrial-impact Last Alert System (ATLAS), I present an alternative approach for searching these sparse photometric datasets for transiting signals. I find this alternative approach to perform tentatively better than traditional methods at detecting transit signals in sparse photometry. Overall, this thesis demonstrates the scientific value in the continued application of citizen science to astronomical problems. The ability to detect new and unusual signals that are overlooked by traditional techniques will continue to be of benefit as data volumes from astronomical surveys grow.

View source

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Trajectory Balance: Improved Credit Assignment in GFlowNets

It is proved that any global minimizer of the trajectory balance objective can define a policy that samples exactly from the target distribution, and empirically demonstrate the benefits of the trajectories balance objective for GFlowNet convergence, diversity of generated samples, and robustness to long action sequenc...

Esmeralda S. Whitammer, Moksh Jain, Emmanuel Bengio et al. · 302 citations · ⚡60

Related blog posts

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.