I'm a third year Astronomy PhD student in CIERA at
Northwestern University working with Prof. Adam A.
Miller. I focus on augmenting large optical time-domain
surveys, like the Zwicky Transient Facility and the
Rubin Obesrvatory, with machine learning tools. In terms
of astrophysics, I'm interested in the large samples
produced by these observatories and observing rare or
rapidly evolving transients. On the machine learning
side, I am particularly excited by computer vision and
multi-modality.
I also work in the DESI Milky Way Survey on modeling the
Milky Way's cumulative mass profile with a
non-parametric tool I developed called NIMBLE.
Research Projects
Presentations of these projects can be found below.
BTSbot: A ConvNet to automatically identify ZTF
transients
Northwestern University, CIERA
The Bright Transient Survey (BTS) relies on
visual inspection ("scanning") to select sources
for accomplishing its mission of
spectroscopically classifying all bright
extragalactic transients found by the Zwicky
Transient Facility (ZTF). BTSbot provides a
bright transient score to individual ZTF alert
packets using their image data and 14 extracted
features. BTSbot eliminates the need for
scanning by automatically identifying new bright
transient candidates. BTSbot outperforms BTS
scanners in terms of completeness (99% vs. 95%)
and identification speed (on average, 7.4 hours
quicker).
Yielded the world's first fully automatic
end-to-end discovery and classification of a
transient:
press release
Some articles writen about BTSbot:
Space.com,
Gizmodo,
Dropbox blogs
Won 1st prize at the Northwestern
CoDEx
Visualization Competition
Gave an oral talk at the Transients and Variable
Universe conference at UIUC:
Slides
Non-Parametric Spherical Jeans Mass Estimation
with B-Splines
University of Michigan – Ann Arbor
We consider the application of Jeans modeling to
mapping the dark matter distribution in the
outer reaches of the Milky Way using field halo
stars. To do so, we develop a novel
non-parametric routine for solving the spherical
Jeans equation by fitting B-splines to the
velocity and density profiles of halo stars and
an MCMC-based subroutine that deconvolves
observational effects from the underlying
distributions.
Presented an iPoster at 237th AAS meeting and
won a Chambliss Astronomy Achievement award.
the iPoster
|
PDF version
Gave an oral talk at the Michigan Institute for
Data Science Poster Symposium 2020 and won the
Outstanding Undergraduate Poster award.
the poster
|
the presentation slides
I wrote a short summary of this project (a bite)
for the undergraduate research series on
astrobites.org
Star Formation Rate in Merger Galaxies
University of Michigan – Ann Arbor
MDM Observatory, Kitt Peak National Observatory
We observe four target merger galaxies in
H-alpha to calcualte their star formation rate
densities and compile previously observed data
giving us their gas surface density. With these
two quantities, we can investigate how various
merger galaxies stand in relation to non-mergers
with respect to the Kennicutt-Schmidt law.
University of Michigan & Leibniz Institute for
Astrophysics
I undertook a project rebuilding the Galaxy,
Halos, Outer disks, Substructure, Thick disks
and Star clusters (GHOSTS) HST survey website. I
noted inefficiencies in the source of the
current version and designed a rebuild to
correct for these and improve expandability. I
proposed my rebuild project to GHOSTS P.I. Dr.
Roelof de Jong with logistical help from GHOSTS
team member and UM professor, Eric Bell. My
rebuild employs
Jinja, an efficient Python templating engine, to
simplify the creation and modification of their
webpages.
When I'm not staring into a jupyter notebook, I like to
keep myself moving and trying new things. During
quarantine, I starting baking all kinds of desserts. In
order to stay fit after eating the desserts, I've taken
up indoor rock climbing.
