While specific academic achievements are not listed, the mention of research directions suggests possible publications in relevant journals and involvement in multiple projects or awards.
Research Experience
Focused on developing and applying advanced AI and machine learning strategies for analyzing large biobank and health data, particularly advancing the study of Alzheimer's disease and related dementias (ADRD). Research areas also encompass integrative analysis of imaging, genetics, and transcriptomics; high-throughput analysis of next-generation sequencing and related biomarker data; innovative integration of disease biomarker research with systems medicine; and extracting actionable insights from complex healthcare data sources.
Education
Specific educational background details are not provided directly.
Background
Research interests include machine learning, medical image computing, biomedical and health informatics, trustworthy AI, NLP/LLMs, network science, imaging genomics, multi-omics and systems biology, Alzheimer’s disease, health disparity, and big data science in biomedicine.
Miscellany
Looking for highly motivated students and scholars with backgrounds in biomedical informatics, computer science, AI/ML, statistics, or engineering to join the lab. Affiliated with several graduate groups including AMCS, BE, GCB, GGEB, and NGG. Openings may be available for undergraduate and graduate students, as well as postdoctoral researchers, subject to funding.