Papers
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. (2017). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea
. (2019). Classifying the unknown: Discovering novel gravitational-wave detector glitches using similarity learning. Physical Review D, 99(8), 082002. https://doi.org/10.1103/PhysRevD.99.082002
. (2020). Knowledge Tracing to Model Learning in Online Citizen Science Projects. Ieee Transactions On Learning Technologies, 13, 123-134. https://doi.org/10.1109/TLT.2019.2936480
transaction paper final figures in text.pdf (1.39 MB). (2020). Teaching Citizen Scientists to Categorize Glitches using Machine-Learning-Guided Training. Computers In Human Behavior, 105, 106198. https://doi.org/10.1016/j.chb.2019.106198
MLGT-preprint.pdf (2.43 MB). (2021). Discovering features in gravitational-wave data through detector characterization, citizen science and machine learning. Classical And Quantum Gravity, 38(19). https://doi.org/10.1088/1361-6382/ac1ccb
. (2023). Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications. Classical And Quantum Gravity, 40(6). https://doi.org/10.1088/1361-6382/acb633
. (2024). Gravity Spy: Lessons Learned and a Path Forward. European Physical Journal Plus, 139, Article 100. https://doi.org/10.1140/epjp/s13360-023-04795-4