Columbia University in the City of New York · Mathematics & StatisticsYingLab
Ying Wei · New York, New York
Research Focus
Ying Wei's lab focuses on understanding Alzheimer's Disease (AD) and related dementias by analyzing genetic data and electronic health records. By using advanced statistical methods and machine learning, the lab aims to identify genetic factors that influence the progression of these diseases over time, particularly as individuals age. This research is crucial for developing better prevention strategies and new treatments for dementia.
Alzheimer's Diseasegenetic architecturemachine learningbiobankselectronic medical recordsage dependencydementia researchdeep learningphenotypingdisease progression
Research Aims
5AIM 01Develop a comprehensive view of the genetic architecture of Alzheimer's Disease across different ages.
AIM 02Integrate genetic data with electronic health records to study disease progression.
AIM 03Enhance statistical power using innovative algorithms for analyzing missing data.
AIM 04Curate age-dependent phenotypes for better understanding of their impact on disease.
AIM 05Address methodological gaps in Phenome-Wide Association Studies.
Skills the Lab Values
statistical modelingdeep learning algorithmsdata imputation techniquesbioinformaticsPython programmingphenome-wide association studiesgraphical modelsdata analysisdata managementmachine learning
Output against the department
Publications205bottom 44% of dept.73rd of 131
this lab
most publishedleast published
Citations12ktop 34% of dept.44th of 131
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.