WUC-program

POSTER SESSION
MELISSA KOHL, Image Classification Using Machine
Learning at LIGO
The Laser Interferometer Gravitational-Wave Observatory
(LIGO) uses interference of light to detect gravitational
waves from black hole and neutron star mergers
millions of light years away. Gravitational waves
are extremely weak compared to vibrations on
Earth, making the detector very sensitive to noise
that can obscure gravitational waves. Currently,
LIGO collaborators transform the transient noise
signals in the LIGO detector data, called
“glitches,” into images called spectrograms,
where different wave signals produce
different shapes. If the source of the glitch
can be determined from the shape, the
glitches are eliminated—reducing noise in
the detector. The source of one classification
of glitch, called a “blip,” remains unknown.
During the summer of 2018, I generated new
spectrograms of blips, discovering six different
shapes. I used machine learning to classify these blips,
creating a foundation for future collaborators to find the
sources of blips and eliminate them.
Faculty Sponsor: Gregory Vaughn-Ogin
ISABEL LA PLAIN, Influence of Heat on mTBI and Associated
Gaze Metrics
Mild traumatic brain injury (mTBI, i.e., concussion), is a
complicated injury caused by biomechanical forces acting on
the brain. It remains unclear why some people struggle with
concussion severity and recovery more than others. Because
intense physical exercise in warm or hot environments
complicates thermoregulation of the brain, I seek to
test whether higher ambient temperature at time of
injury exacerbates the effects of concussion. I used
video-oculography (eye tracking) and accelerometers
to measure combined eye and head gaze movements
of athletes before and after concussion. I present
a discussion of the degrees of difference in these
movements following mTBI. My findings will help inform
concussion prevention and recovery.
Faculty Sponsor: Thomas Knight
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