Novel analytic strategies are also being developed to analyze big unstructured data to identify potential digital biomarkers that are predictive of future health outcomes. We are integrating active engagement with passive engagement technologies from the habitual environment to make sustained monitoring feasible. We have deployed thousands of wearable devices and mobile apps to monitor cardiovascular health and cognitive health. Exploration of digital and wearable devices for health monitoring.In combination with neuroimaging and blood-based measures, we are also developing multimodal machine learning methods to identify new biomarkers that are predictive of future cognitive impairment. We have built multiple machine learning models to predict dementia risk from midlife risk factors and neuropsychological tests. Development of machine learning models for early disease diagnosis.We are also developing computational methods to integrate different molecular signatures and build gene interaction networks to study potential disease regulation networks. We have identified numerous molecular signatures from gene expression, protein expression, and DNA methylation that are related to aging and cardiovascular disease. Complex diseases are usually caused by the interplay of genetic and environmental factors. Integration of multi-omics data to understand disease molecular mechanisms.These studies have identified hundreds of genetic loci associated with atrial fibrillation, heart failure, hypertension, and Alzheimer’s disease. We have been involved in multiple large-scale genetic consortiums, such as the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Trans-Omics for Precision Medicine (TOPMed) program, and Alzheimer's Disease Sequencing Project (ADSP). Identification of genetic causes of complex diseases.Our lab is mainly focused on the development and application of computational tools to study complex diseases. I am a bioinformatician/biostatistician with training in mathematics, machine learning, genetics, and digital medicine.
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