Xinhui Li

My name is Xinhui Li (黎欣惠). I am a fifth-year Ph.D. candidate in Electrical and Computer Engineering at Georgia Institute of Technology and Center for Translational Research in Neuroimaging and Data Science (TReNDS), advised by Prof. Vince D. Calhoun and Dr. Rogers F. Silva. During my PhD, I interned at Amazon Science working on video understanding with vision-language models. Previously, I developed a software pipeline C-PAC for MRI preprocessing and investigated interpipeline agreement at Child Mind Institute. I am actively seeking full-time Research Scientist opportunities in industry and academia.

I used to be an engineer dreaming of connecting the brain and the computer, and now I am growing as a scientist attempting to solve fundamental problems in neuroscience and computer science. My current research interests include representation learning, generative modeling, multimodal neuroimaging analysis, and AI for health and science. To gain a comprehensive understanding of the brain, I am developing a deep multidataset subspace analysis framework that includes linear and nonlinear latent variable models (ICA/IVA/ISA) to learn linked and identifiable representations from multimodal neuroimaging datasets. Lately, I have become interested in AI safety. I believe safe AI is a prerequisite of beneficial AI. More generally, I am fascinated by both biological and artificial intelligence. I think understanding the principles of neural computation will likely help us develop more flexible algorithms and build more energy-efficient machines. Please feel free to reach out if you want to discuss research questions or collaboration opportunities.

I love art in many forms. I often spend my free time at museums and theaters. I also collaborate with talented artists to create artwork related to my research, such as Butterfly Effect and Schizosymphony.