Fellows Spotlight: Amiee Huang
Research focus: Statistical and machine learning tools to empower the study of real-world evidence
Can you describe your background and where you came from before the fellowship?
I obtained both my BSc and PhD in Statistics from the University of Hong Kong in 2018 and 2023, with a research focus on the analysis of sequential data, such as textual streams and financial time series.
What does your current research focus on, and who do you work with?
My current research focuses on three central questions: (1) How can medical knowledge from diverse modalities be effectively aligned and represented while addressing nuances such as privacy concerns? (2) How can enhanced representations be utilized to develop robust AI-based algorithms for complex phenotyping in a label-efficient manner? (3) How can phenotyping algorithms be leveraged to curate real-world evidence with necessary correction of biases? I work closely with Prof. Florence Bourgeois and Prof. Tianxi Cai, physicians from Mass General Brigham and University of Pittsburgh Medical Center and many other amazing collaborators.
Where do you plan to go next?
I will be entering the job market in 2025-2026 and am currently open to opportunities in both industry and academia.