Xiaobo Li

Xiaobo Li is a Professor in the Department of Bio-Medical Engineering at the New Jersey Institute of Technology (NJIT). His research focuses on neurological disorders including Attention-Deficit/Hyperactivity Disorder (ADHD) and schizophrenia, with emphasis on neuroimaging analysis, brain network characterization, and machine learning applications. He has led NIH-funded projects investigating familial ADHD neural correlates and remission mechanisms (2016-2022).

Key research areas involve integrating neuroimaging data (fMRI, MRI) with computational models to understand disease mechanisms. His work combines structural brain analysis, graph-based algorithms, and deep learning techniques to identify biomarkers for mental health conditions. Over 90 peer-reviewed publications and 2568 citations reflect his impactful contributions to translational neuroscience.

• Grant Highlights:
• Neural Correlates of Familial and Non-familial ADHD (NIH 2019-2022)
• Neuroanatomical Markers Of Persistence Versus Remission Of ADHD (NIH 2016-2019)

Publications emphasize schizophrenia subtype classification, ADHD neuroanatomical differences, and multimodal data integration. His research bridges computational methods with clinical neuroscience to advance diagnostic tools and therapeutic understanding.