Paper Competition Winners

JSM 2024 Student Paper Competition

The student paper competition finalists at JSM 2024 in Portland, OR

The student paper competition finalists at JSM 2022 in Washington, D.C.

Winner
Andrew Kahlil Saydjari (Harvard) Photometry on Structured Backgrounds: Local Pixelwise Infilling by Regression
Saydjari, A. K. & Finkbeiner, D. P., 2022, ApJ, 933, 155
Finalists
- Aarya Anil Patil (Toronto) Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67
  Patil, A. A., Bovy, J., Eadie, G., & Jaimungal, S., 2022, ApJ, 926, 51
- Maximilian Autenrieth (ICL) Supervised Learning and Hierarchical Bayesian Modeling Under Covariate Shift in Supernova Cosmology
  Autenrieth, M., van Dyk, D. A., Trotta, R., & Stenning, D. C., 2021, arXiv e-print
- Jeff Shen (Toronto) The Mass of the Milky Way from the H3 Survey
  Shen, J., Eadie, G. M., Murray, N., Zaritsky, D., Speagle, J. S., Ting, Y.-S., Conroy, C., Cargile, P. A., Johnson, B. D., Naidu, R. P., & Han, J. J., 2022, ApJ, 925, 1
- Stephen Thorp (Cambridge) Testing the Consistency of Dust Laws in SN Ia Host Galaxies: A BayeSN Examination of Foundation DR1
  Thorp, S., Mandel, K. S., Jones, D. O., Ward, S. M., & Narayan, G., 2021, MNRAS, 508, 4310

We thank The Gordon & Betty Moore Foundation for financial support for the Finalists’ travel to attend and present at JSM.

Winner
Alex Gagliano (UIUC) GHOST: Using Only Host Galaxy Information to Accurately Associate and Distinguish Supernovae
Gagliano, A., Narayan, G., Engel, A., Carrasco Kind, M., LSST Dark Energy Science Collaboration, 2021, ApJ, 908, 170
Finalists
- Karthik Reddy (UMaryland) X-Ray-to-Radio Offset Inference from Low-Count X-Ray Jets
  Reddy, K., Georganopoulos, M., & Meyer, E.T., 2021, ApJS, 253, 37
- Lu Li (Shanghai Obs) Modeling unresolved binaries of open clusters in the color-magnitude diagram
  Li, L., Shao, Z., Li, Z.-Z., Yu, J., Zhong, J., & Chen, L., 2020, ApJ, 901, 49
- Matt Nixon (Cambridge) Assessment of Supervised Machine Learning for Atmospheric Retrieval of Exoplanets
  Nixon, M.C., & Madhusudan, N., 2020, MNRAS, 496, 269
- Willow Fox-Fortino (UPenn) Reducing ground-based astrometric errors with Gaia and Gaussian processes
  Fortino, W.F., et al., arXiv:2010.13742

See the Session Program for abstracts and schedule.

Winner
Josh Speagle (Harvard) – Photometric Biases in Modern Surveys
Portillo, S.K.N., Speagle, J.S., & Finkbeiner, D.P., 2020, AJ, 159, 165
Finalists
- Richard Feder-Staehle (Cal Tech) – Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending
  Feder, R.M., Portillo, S.K.N., Daylan, T., & Finkbeiner, D., 2020, AJ, 159, 163
- Matthew Ho (Carnegie Mellon) – A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
  Ho, M., Rau, M.M., Ntampaka, M., Farahi, A., Trac, H., & Poczos, B., 2019, ApJ, 887, 25
- Oliver Philcox (Princeton) – Inferring Galactic Parameters from Chemical Abundances: A Multi-Star Approach
  Philcox, O., & Rybicki, J., 2019, ApJ, 887, 9
- Collin Politsch (Carnegie Mellon) – Trend Filtering: A Modern Statistical Tool for Time-Domain Astronomy and Astronomical Spectroscopy
  Politsch, C., Cisewski-Kehe, J., Croft, R.A.C., & Wasserman, L., 2020, MNRAS, 492, 4005

The finalists await Prof. Chad Schafer to reveal the winner of the student paper competition at JSM 2019 in Denver, CO.

See the Session Program for abstracts and more information.

Winner – Axel Widmark
Widmark, A., 2019, A&A, 623, A30, Measuring the local matter density using Gaia DR2
Finalist – Francesca Capel, KTH Royal Institute if Technology
Capel, F. & Mortlock, D.J., 2019, MNRAS, 484, 2324, Impact of using the ultrahigh-energy cosmic ray arrival energies to constrain source associations
Finalist – Daniel Muthukrishna, University of Cambridge
Muthukrishna, D., Narayan, G., Mandel, K.S., Biswas, R., and Hlozek, R., 2019, arXiv: 1904.00014, RAPID: Early Classification of Explosive Transients using Deep Learning
Finalist – Xixi Yu, Imperial College of Science & Technology
Yu, X., Del Zanna, G., Stenning, D.C., Cisewski-Kehe, J., Kashyap, V.L., Stein, N., van Dyk, D.A., Warren, H.P., and Weber, M.A., 2018, ApJ, 866, 146, Incorporating Uncertainties in Atomic Data into the Analysis of Solar and Stellar Observations:A Case Study in FeXIII