About Me

I am a NASA Hubble Fellow in the Department of Astrophysical Sciences at Princeton.

My research focuses on combining astrophysics, statistics, and high-performance coding to study the chemical, spatial, and kinematic variations in the dust that permeates the Milky Way. This dust is an important building block in matter assembly (formation of stars and planets), driver of the interstellar environment, and Galactic foreground. To do this, I use spectroscopic and imaging surveys containing millions and billions of stars, respectively.

I believe knowledge comes from data, and data comes from instruments- a view that shapes my approach to science. This ethos of work has earned me "Architect" status in SDSS-V. I am passionate about scientific communication, open source software/data availability, and the replication crisis. I am also a Julia programming language enthusiast. Please reach out to me if you want to collaborate or have any questions related to my research!

In previous careers, I have also been a chemist (spectroscopy, organometalic, polymers) and condensed matter physicist (InAs/HgCdTe superconductor-semiconductor fabrication and dilution refrigerator measurement) and have deeply loved each of these roles.

Selected Projects

DECaPS2: The Dark Energy Camera Plane Survey DR2

I led the data reduction for the second and final release of the Dark Energy Camera Plane Survey (DECaPS2). We provide a catalog of 3.32 billion sources in our survey footprint that covers 6.5% of the sky. We developed new methods well-suited to photometry in the Galactic plane, developed improved measures of photometric depth adapted to crowded-fields, and validate our pipeline extensively with synthetic star tests. For more, see our project website. Tip: See how far you can zoom in! (be patient)

APOGEE Spectral Decomposition

I developed and applied a new pipeline to the reduce SDSS-V APOGEE spectra that separates each visit into a linear combination of the most probable contributions from the sky, star, and ISM. This component separation approach to spectral reduction represents a paradigm shift from commiting to single point estimates (of the telluric absorption, sky emission lines, etc.) to marginalzing over our uncertainty about the contribution of each component to the overall spectrum in a joint fit that produces dense posteriors. The goals of this project are to measure the strong diffuse interestellar band near 15273 Å, discover new DIBs, reduce biases in stellar parameter and abundance measurements, and obtain robust parameter measurements of spectroscopic multiples.

Diffuse Interstellar Band in Gaia DR3 RVS Spectra

I developed and applied a new pipeline to the Gaia (DR3) RVS spectra to measure the diffuse interstellar band (DIB) near 862.1 nm. This method marginalized over stellar types, avoiding false detections of stellar residuals as DIB detections, as in the public Gaia catalog. This analysis allowed us to show that there were no statistically significant detections of DIBs in the Local Bubble. For more, see our project website.

High Angular Resolution 3D Dust Mapping

I extended a previous dustmaping methodology using bayestar and am combinining that with deep, high-quality NIR photometry from DECaPS2 (see above) to achieve an extraordinarily high angular resolution 3D dust map, 5x the resolution of the 2D Planck dust map! Through this careful statistical inference, we expect to see ~ pc scale structures several kpc away in nearby spiral arms of the Galaxy. The GIF above shows the improvement in angular resolution acheived by our 3D dust map compared to a previous version (Bayestar19) and the video below shows only a 4° x 4° region in the footprint of the map, which will cover the entire southern Galactic plane!