BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//wp-events-plugin.com//7.4.2//EN
TZID:America/Los_Angeles
X-WR-TIMEZONE:America/Los_Angeles
BEGIN:VEVENT
UID:359@escience.washington.edu
DTSTART;TZID=America/Los_Angeles:20260415T163000
DTEND;TZID=America/Los_Angeles:20260415T172000
DTSTAMP:20260414T173401Z
URL:https://escience.washington.edu/events/uw-data-science-seminar-aoi-hun
 saker/
SUMMARY:UW Data Science Seminar: Aoi Hunsaker
DESCRIPTION:Please join us for a UW Data Science Seminar featuring UW Psych
 ology Ph.D. student Aoi Hunsaker on Wednesday\, April 15th from 4:30 to 5:
 20 p.m. PT. The seminar will be held in IEB G109.\n"On testing hearing sen
 sitivity across the animal kingdom more quickly and accurately"\nAbstract:
  I study what sounds animals can hear by recording brain responses while I
  play sounds over a speaker. This kind of test is called the Auditory Evok
 ed Potential (AEP) test. There is a need in my field to do these recording
 s more quickly and accurately. Currently\, AEP tests take over an hour to 
 complete for a single subject. Thus\, for animals that are sensitive to ex
 perimental handling\, comprehensive auditory testing is not currently poss
 ible. Furthermore\, the sensitivity of an animal's hearing is commonly det
 ermined by an experimenter visually inspecting the brain response waveform
 s. This method of response detection is subjective and can possibly lead t
 o inaccurate estimations of auditory sensitivity. In the AI and Data Scien
 ce Accelerator Program\, I worked with Dr. Ariel Rokem to develop a softwa
 re tool that implements an automated response detection algorithm and mode
 l-based auditory threshold estimation during testing. The response detecti
 on algorithm involves comparing bootstrapped distributions of auditory res
 ponse strengths when the sound is ON vs. OFF. Threshold estimation involve
 s fitting the lower half of a hard-sigmoid to auditory response strength d
 ata plotted against stimulus intensity and defining the threshold as the e
 lbow point in the model. Throughout my participation in the Data Science a
 nd AI Accelerator program\, I learned in greater detail about useful stati
 stical methods such as bootstrapping and model fitting. Furthermore\, I le
 arned good practices in writing software such as writing tests and modular
 izing code.\n\nSpeaker Bio: Aoi Hunsaker is a PhD Student in the Departmen
 t of Psychology in the Neural Systems and Behavior Program at the Universi
 ty of Washington. Her research focus is creating hardware and software ele
 ctrophysiology tools to study the auditory sensitivity in animals. Through
  her mentorship with Dr. Ariel Rokem in the eScience AI and Data Accelerat
 or program\, she learned essential software engineering and data analysis 
 methods relevant to electrophysiology and psychophysics. These skills have
  been instrumental in her work developing a software tool which measures a
 nd analyzes the neural activity of animals while listening to sounds.\n\n\
 nThe 2025-2026 seminars will be held in person\, and are free and open to 
 the public.\n\n
ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa
 ds/2026/04/profilePhoto-e1776187930662.jpg
END:VEVENT
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
X-LIC-LOCATION:America/Los_Angeles
BEGIN:DAYLIGHT
DTSTART:20260308T030000
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
END:DAYLIGHT
END:VTIMEZONE
END:VCALENDAR