Helen Qu

helenqu [at] sas.upenn.edu

Google Scholar LinkedIn

broken photo :(

I am a fourth year PhD candidate in Physics at the University of Pennsylvania, advised by Dr. Masao Sako. I work on machine learning applications to cosmology, specifically with type Ia supernovae as cosmological probes. I am part of the Dark Energy Survey Collaboration as well as the Nancy Grace Roman Space Telescope supernova science investigation team. I am particularly interested in developing deep learning methods with large-scale astronomical survey data applications in mind.

Publications

A Convolutional Neural Network Approach to Supernova Time-Series Classification
International Conference on Machine Learning (ICML) 2022 Workshop on Machine Learning for Astrophysics
Helen Qu, Masao Sako, Anais Möller, Cyrille Doux

Photometric Classification of Early-Time Supernova Lightcurves with SCONE
Astronomical Journal, 2022
Helen Qu, Masao Sako

SCONE: Supernova Classification with a Convolutional Neural Network
Astronomical Journal, 2021
Helen Qu, Masao Sako, Anais Möller, Cyrille Doux

There’s no difference: Convolutional Neural Networks for transient detection without template subtraction
arXiv, 2022
Tatiana Acero-Cuellar, Federica Bianco, Greg Dobler, Masao Sako, Helen Qu

The Pantheon+ Analysis: Cosmological Constraints
Astrophysical Journal, 2022
Dillon Brout, Dan Scolnic, Brodie Popovic, …, Helen Qu, et al.

The Pantheon+ Analysis: SuperCal-Fragilistic Cross Calibration, Retrained SALT2 Light Curve Model, and Calibration Systematic Uncertainty
Astrophysical Journal, 2022
Dillon Brout, Georgie Taylor, Dan Scolnic, …, Helen Qu, et al.

A Reference Survey for Supernova Cosmology with the Nancy Grace Roman Space Telescope
arXiv, 2021
Benjamin M. Rose, Charles Baltay, Rebekah Hounsell, …, Helen Qu, et al.

Synergies between Vera C. Rubin Observatory, Nancy Grace Roman Space Telescope, and Euclid Mission: Constraining Dark Energy with Type Ia Supernovae
arXiv, 2021
Benjamin M. Rose, Greg Aldering, Mi Dai, …, Helen Qu

Selected Talks

A Convolutional Neural Network Approach to Supernova Time-Series Classification
Rising Stars in Data Science (15 November 2022)

Classifying Supernova Time-Series Photometry with Convolutional Neural Networks
International Conference on Machine Learning for Astrophysics (1 June 2022)

Building the Toolbox for Type Ia Supernova Cosmology
Invited Seminar Talk, University of Delaware (8 March 2022)

Photometric Supernova Classification in the Roman Era
Roman Time Domain Conference (8 February 2022)

SN Ia Cosmology and Core-Collapse Science with the Roman Space Telescope
American Astronomical Society meeting (27 January 2022)

Misc.

I completed a BSE in Computer Science at Penn. I have also spent some time as a software engineer at Academia.edu, Internet.org by Facebook, and Yahoo.

Outside of research, I love to bake and eat and occasionally make music.