Collaborating Cores
Bioinformatics and Biostatistics Core
Eunyoung Angela Lee, PhD – Assistant Professor
Education & Training
MS Biostatistics, Gillings School of Public Health, University of North Carolina at Chapel Hill – Chapel Hill, North Carolina
PhD Medical Sciences and Biomedical Informatics, Ajou University – Suwon, South Korea
Areas of Interest
Research interests: Development of statistical and machine learning methods for complex biomedical data analysis (imaging, EHRs), including feature selection, predictive modeling, and network analysis, and translational research in aging, neurodegenerative diseases, and mental health
Clinical interests: Patient heterogeneity characterization for precision medicine and personalized therapeutic strategies, and statistical methods for early disease screening and prevention in neurodegenerative disorders
Research & Experience
As a computational biostatistician, I specialize in developing and applying advanced statistical methodologies to analyze complex biomedical data, with particular emphasis on neurodegenerative conditions and brain aging. My research integrates diverse clinical data sources, including electronic health records, neuroimaging, and longitudinal cohort studies, to decode disease mechanisms and progression patterns. I employ innovative statistical approaches for temporal modeling of disease trajectories, identification of novel disease subtypes, and development of precision medicine strategies. My methodological work spans machine learning, network analysis, and statistical modeling, with applications in early detection and risk stratification. Through rigorous statistical frameworks and computational methods, my research aims to advance our understanding of age-related diseases and translate these insights into actionable clinical strategies for improved patient outcomes.
Hobbies & Interests
Baseball enthusiast, aspiring golfer, and avid explorer of YouTube’s endless offerings.
Akram Yazdani, PhD, MSc – Assistant Professor
Education & Training
MSc Statistics (probabilistic multilevel modeling for complex data), Shahid Beheshti University – Tehran, Iran
PhD Statistical Sciences (machine learning and Bayesian modeling for large-scale genomics), University of Padova – Padova, Italy
Postdoc Human Genetics, The University of Texas Health Science Center at Houston – Houston, TX
Postdoc Neuroscience, Icahn School of Medicine at Mount Sinai – Manhattan, NY
Prior Scientific Appointments
Research Scientist Cancer Pharmacogenomics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill – Chapel Hill, NC
Research Interests
My research interests lie at the intersection of artificial intelligence/machine learning (AI/ML) and molecular medicine. My work focuses on developing AI/ML computational algorithms to analyze large-scale molecular data and link them to clinical outcomes, with the aim of better understanding disease progression, response to treatment, and disease subtypes, particularly in cancer, neurological and neuropsychiatric disorders, and cardiovascular diseases. My algorithms are centered around regularization techniques, Bayesian probabilistic models, and deep learning to optimize the analysis of complex datasets, ensuring reproducible and interpretable results. I am a member of the Translational Medicine Subcommittee of the Southwest Oncology Group (SWOG). I have led multidisciplinary research initiatives focused on integrative multi-omics, leveraging large-scale data from SWOG, the Alliance for Clinical Trials in Oncology, and Trans-Omics for Precision Medicine (TOPMed).