Zhongming Zhao

Dr. Zhao has broad interests in the area of genomics, deep learning, precision medicine, translational science, and big data science. We develop novel computational approaches for deep understanding genetic variants and regulatory mechanisms in complex disease. Representative projects are below. The students may work with Dr. Zhao to identify a long-term project for thesis. Multi-Scale, Integrated, and Contextualized Approaches for Complex Disease. In this NIH-funded project, we will develop and implement a robust AI framework, namely AIM-AI, for transforming the genetic catalog of Alzheimer’s disease (AD) in a way that is Actionable, Integrated and Multiscale. We will engineer novel deep learning algorithms and GPT-based foundational models to build a powerful brain molecular chronological age predictor and further to dissect cell-type specific, genetic regulatory mechanisms in complex disease like AD. Predicting Phenotype by Deep Learning Heterogeneous Multi-Omics Data. We combine bioinformatics, statistical genetics, and phenotype and electronic medical record (EMR) data mining to develop novel analytical strategies that maximally leverage regulatory information from both genotype and expression (spatiotemporal and single cell levels). Precision medicine in cancer Since 2009, our lab has applied next-generation sequencing to discover actionable mutations in cancer, developed bioinformatics and computational approaches to detect cancer driver mutations and genes from massive cancer genomic data, and developed pharmacogenomics approaches to identify existing drugs for new disease (drug repositioning).