Xinhui Li

Me and Cactus Simpson, Huntington Garden, Spring 2023

I am a third-year Ph.D. student in Electrical and Computer Engineering at the Georgia Institute of Technology and the Center for Translational Research in Neuroimaging and Data Science (TReNDS), advised by Dr. Vince Calhoun and Dr. Rogers Silva. Previously, I worked as a research engineer at the Child Mind Institute, where I developed a software pipeline C-PAC for MRI preprocessing and analysis.

I used to be an engineer dreaming to connect brains and computers, now I am growing as a scientist attempting to solve fundamental questions in neuroscience and computer science. My current research interests include multimodal neuroimaging and unsupervised representation learning. To better understand different aspects of brains, I am developing a multidataset subspace analysis framework including both linear and nonlinear latent variable models to identify linked sources from multimodal neuroimaging datasets. Apart from my job, I am curious about biological and artificial intelligent algorithms and systems. I believe that understanding the principles of neural computation will help us to develop more flexible artificial intelligence algorithms and build more energy-efficient machines.

Please feel free to reach out if you want to discuss any questions or collaboration opportunities. I would also love to hear your feedback so I can learn and grow.

news

Aug 24, 2023	Two abstracts on multimodal subspace independent vector analysis (MSIVA) and deep independent vector analysis (DIVA) are accepted at RSBC 2023
Jun 19, 2023	Two papers are accepted at ICML 2023 workshops: Learning pipeline-invariant representation for robust brain phenotype prediction (Data-centric Machine Learning Research Workshop) Predictive Sparse Manifold Transform (Workshop on High-dimensional Learning Dynamics)
Mar 13, 2023	Three abstracts are accepted at OHBM 2023
Jan 22, 2023	Two papers are accepted at ISBI 2023: Evaluating trade-offs in IVA of multimodal neuroimaging using cross-platform multidataset independent subspace analysis (oral) Multimodal subspace independent vector analysis better captures hidden relationships in multimodal neuroimaging data
Dec 1, 2022	I am honored and humbled to receive the Cadence Diversity in Technology Scholarship. It means a lot to me that my experience could inspire the next generation of women in techology.
Oct 22, 2022	Our paper Pipeline-Invariant Representation Learning for Neuroimaging is accepted at NeurIPS ML4H Symposium 2022. Looking forward to the trip to NOLA!
Jul 16, 2022	I start working as the website and communications manager in the OHBM BrainArt Special Interest Group! I hope to promote the communications between neuroscientists and artists, and ultimately promote the interaction between neuroscience and art.