My research focuses on developing an analytic platform that assesses the aging of brain structures and their structural and functional networks as well as predicting the eventual long-term outcome for neurodevelopment and quantifying the progression of neurodegeneration. To follow-up long-term brain structural modification associated with neurodevelopmental/neurodegenerative disorders, my group develops methods to quantify various aspects of brain anatomical and networking variability using longitudinally collected multi-contrast MRI. My technical expertise on surface-based morphology and texture modeling, network topology analysis, and multivariate statistical modeling consists of essential elements to develop a combination of techniques to accomplish the proposed specific aims. Using advanced pattern analytic approaches with machine learning and deep learning on multi-contrast MRI features, my current research seeks to understand the atypical structural and network alterations in various neurological diseases including sleep disorders, epilepsy, dementia, and preterm birth and ultimately to predict neurological/brain functional outcome in the patients. I serve as the Principal Investigator at the NeuroImaging with Deep Learning Lab (NIDLL), and coordinate research efforts, engage with NIH program officials as appropriate, and guides and coordinates the research efforts of the lab members. We welcome you to join the lab and participate in our valuable research. Laboratory of Neuro Imaging, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA. Electronic address: email@example.com.