Xinhui Li

My name is Xinhui Li (黎欣惠). I am a postdoctoral researcher at the Center for Translational Research in Neuroimaging and Data Science (TReNDS). I completed my Ph.D. at the Georgia Institute of Technology, advised by Prof. Vince D. Calhoun and Dr. Rogers F. Silva. During my Ph.D., I interned as a data scientist at Amazon. Previously, I worked as a research engineer at the Child Mind Institute, advised by Dr. Michael P. Milham and Dr. Ting Xu.

I work at the intersection of machine learning and computational neuroscience, developing methods and tools for large-scale neuroimaging analysis to better understand the brain and its disorders.

• Multimodal Representation Learning: I develop multimodal fusion methods that learn latent representations from high-dimensional, multimodal neuroimaging data, with a focus on identifying phenotypic and neuropsychiatric biomarkers.
  • Related work: Multimodal Subspace Independent Vector Analysis, Multimodal Independent Vector Analysis, Torch-MISA
• AI for Mental Health: I design generative models, agentic systems, and neuroimaging-based metrics for characterizing and assessing neuropsychiatric disorders, with the goal of improving diagnosis and treatment of mental illness.
  • Related work: Functional Network Connectivity Interpolation, AI Psychiatrist Assistant, Brainwide Risk Score
• Open and Reproducible Science: As a first-generation scholar, I am committed to creating an open, collaborative research culture. I study variability in neuroimaging preprocessing pipelines and contribute to open-source tools and standards to improve the reproducibility and reliability of neuroimaging analysis.
  • Related work: Interpipeline Agreement, C-PAC, NMIND
• Cross-Species Neuroimaging: I build deep learning models for brain extraction and segmentation across species, including non-human primate MRI.
  • Related work: DeepBet, DeepSeg

I love art in many forms. I often spend my free time at museums and theaters. I collaborate with talented artists to create artwork related to my research, such as Butterfly Effect and Schizosymphony. Please feel free to reach out if you want to discuss research questions or collaboration opportunities.