I am a Ph.D. student in applied statistics at the University of Technology Sydney. The purpose of my resarch is to train a machine learning algorithm to instantly determine the severity level of a patient with aphasia (a communiation impairment cause by stroke or traumatic brain injury) in an effort to reduce costs, save time and provide an easier and more manageble assessment for patients with aphasia.
natural language processing
Master of Science (Honours) - Mathematical and Statistical Modelling
Graduate Certificate in Mathematics
Bachelor of Business - Economics
Prizes, awards and special recognition
ACEMS Outstanding Achievements Recognition Award was awarded to Tea Uggen. Awarded from the ACEMS.
From https://news.eis.uow.edu.au/j-b-douglas-awards-day-2018/: As usual the standard of presentations was very high. This year’s prize was awarded to Tea Uggen (4th from left in group photo) from the School of Mathematical Sciences at UTS.
Also check ACEMS article: https://acems.org.au/news/tea-uggen-jb-douglas-award
IBC 2018 Young Statisticians' Showcase was awarded to Tea Uggen. Awarded from the International Biometric Society (IBS).
Selected to represent the Australasian region and present my PhD research in the IBC 2018 Young Statisticians' Showcase Competition