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Milky Way Galaxy
Credit: H F Stevance

Dr Heloise Stevance

Schmidt AI in Science Fellow

Research theme

  • Astronomy and astrophysics

Sub department

  • Astrophysics
heloise.stevance@physics.ox.ac.uk
hfstevance.com
  • About
  • Research
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  • Prizes, awards and recognition
  • Publications

The ATLAS Virtual Research Assistant

The Astrophysical Journal American Astronomical Society 990:2 (2025) 201

Authors:

HF Stevance, KW Smith, SJ Smartt, SJ Roberts, N Erasmus, DR Young, A Clocchiatti

Abstract:

We present the Virtual Research Assistant (VRA) of the ATLAS sky survey, which performs preliminary eyeballing on our clean transient data stream. The VRA uses histogram-based gradient-boosted decision tree classifiers trained on real data to score incoming alerts on two axes: “Real” and “Galactic.” The alerts are then ranked using a geometric distance such that the most “real” and “extragalactic” receive high scores; the scores are updated when new lightcurve data is obtained on subsequent visits. To assess the quality of the training we use the recall at rank K, which is more informative to our science goal than general metrics (e.g., accuracy, F1-scores). We also establish benchmarks for our metric based on the pre-VRA eyeballing strategy, to ensure our models provide notable improvements before being added to the ATLAS pipeline. Then, policies are defined on the ranked list to select the most promising alerts for humans to eyeball and to automatically remove bogus alerts. In production the VRA method has resulted in a reduction in eyeballing workload by 85% with a loss of follow-up opportunity <0.08%. It also allows us to automatically trigger follow-up observations with the Lesedi telescope, paving the way toward automated methods that will be required in the era of LSST. Finally, this is a demonstration that feature-based methods remain extremely relevant in our field, being trainable on only a few thousand samples and highly interpretable; they also offer a direct way to inject expertise into models through feature engineering.
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The Heavy Element Enrichment History of the Universe from Neutron Star Mergers with Habitable Worlds Observatory

(2025)

Authors:

Eric Burns, Jennifer Andrews, Robert Szabo, Brad Cenko, Paul O'Brien, Heloise Stevance, Ian Roederer, Mark Elowitz, Om Sharan Salafia, Luca Fossati, Margarita Karovska, Eunjeong Lee, Gijs Nelemans, Igor Andreoni, Filippo D'Ammando, Pranav Nalamwar, Brendan O'Connor, Griffin Hosseinzadeh, Eliza Neights, Endre Takacs, Melinda Soares-Furtado, Maria Babiuc Hamilton, Borja Anguiano, Stà phane Blondin, Frank Soboczenski, Shivani Shah
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The ATLAS Virtual Research Assistant

(2025)

Authors:

HF Stevance, KW Smith, SJ Smartt, SJ Roberts, N Erasmus, DR Young, A Clocchiatti
More details from the publisher
Details from ArXiV

A Python client for the ATLAS API

(2025)

Authors:

Heloise F Stevance, Jack Leland, Ken W Smith
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Search for the Optical Counterpart of Einstein Probe Discovered Fast X-ray Transients from Lulin Observatory

(2025)

Authors:

Amar Aryan, Ting-Wan Chen, Sheng Yang, James H Gillanders, Albert KH Kong, SJ Smartt, Heloise F Stevance, Yi-Jung Yang, Aysha Aamer, Rahul Gupta, Lele Fan, Wei-Jie Hou, Hsiang-Yao Hsiao, Amit Kumar, Cheng-Han Lai, Meng-Han Lee, Yu-Hsing Lee, Hung-Chin Lin, Chi-Sheng Lin, Chow-Choong Ngeow, Matt Nicholl, Yen-Chen Pan, Shashi Bhushan Pandey, Aiswarya Sankar K, Shubham Srivastav, Guanghui Sun, Ze-Ning Wang
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