Trinity Fan

Trinity Fan is an Applied Scientist II at Amazon, currently advancing toward a PhD in Statistics at the University of Washington. With a strong background in Bayesian methods and statistical modeling, they have contributed to innovative research on cause of death prediction from narratives. Previously, Trinity served as a Machine Learning Scientist Intern at American Family Insurance, where they developed systems to detect hallucinations in large language models. Their experience also includes roles as a Research Assistant and Teaching Assistant at both the University of Washington and the University of British Columbia, enhancing their expertise in data science and statistical methodologies.