Principal Investigator, Associate Professor
Associate Professor, Department of Biomedical Engineering
Associate Professor, Division of Electrical and Computer Engineering
Principal Investigator, Laboratory of Integrated Brain Imaging
Director, Engineering Preclinical Imaging Center
Zhongming Liu received B.S. (2000) in Electrical Engineering and M.S. (2003) in Control Science and Engineering from Zhejiang University, and Ph.D. (2008) in Biomedical Engineering from the University of Minnesota advised by Bin He. From 2009 to 2013, he worked with Jeff Duyn as a research fellow in the Advanced MRI Section at the National Institutes of Health. From 2013 to 2019, he was an Assistant/Associate Professor of Biomedical Engineering and Electrical and Computer Engineering at Purdue University. In 2020, he moved to the University of Michigan as an Associate Professor in the Department of Biomedical Engineering, the Electrical and Computer Engineering Division of the Department of Electrical Engineering and Computer Science. At U-M, he is also the Director of Engineering Preclinical Imaging Center and a faculty member affiliated with Michigan Institute of Data Science, Michigan Neuroscience Institute, Neuroscience Graduate Program, and Precision Health Initiative. He is a Senior Member of IEEE, Associate Editor for IEEE Transactions on Biomedical Engineering, Frontiers in Neuroscience, and Editorial Board Member for NeuroImage. His lab develops and uses advanced techniques for imaging, recording, stimulating and modeling the brain to accelerate progress in neurosciences, neural engineering, and artificial intelligence. His research has been continuously funded by NIH, NSF, DARPA among others, and has been recognized with a number of awards, including the Innovative New Scientist in Biobehavioral Research from National Institute of Mental Health, Faculty Award of Excellence from Purdue University, Best Dissertation Award from University of Minnesota, and >20 paper or abstract awards from international conferences.
Recent Publications (see the full list in google scholar)
- Wang X, Cao J, Han K, Choi M, She Y, Scheven UM, Recep Avci, Du P, Cheng L, Di Natale MR, Furness JB, Liu Z, "Diffeomorphic surface modeling for MRI-based characterization of gastric anatomy and motility," IEEE Transactions on Biomedical Engineering, in press.
- Cao J, Wang X, Chen JD, Zhang N, Liu Z, "The vagus nerve mediates the stomach-brain coherence in rats," NeuroImage, 263: 119628, 2022.
- Cao J, Wang X, Powley TL, Liu Z, "Gastric neurons in the nucleus tractus solitarius are selective to the orientation of gastric electrical stimulation," Journal of Neural Engineering, 18:056066, 2021.
- Zhang Y, Choi M, Han K, Liu Z, "Explainable semantic space by grounding language to vision with cross-modal contrastive learning," Advances in Neural Information Processing Systems (NeurIPS), 2021.
- Kim J-H, Zhang Y, Han K, Wen Z, Choi M, Liu Z., “Representation learning of resting state fMRI with variational auto-encoder,” NeuroImage, 241: 118423, 2021.
- Zhang Y, Han K, Worth RM, Liu Z, “Connecting concepts in the brain by mapping cortical representations of semantic relations,” Nature Communications, 11:1877, 2020.
- Han K, Wen H, Shi J, Lu K-H, Zhang Y, Di F, Liu Z, "Variational auto-encoder: an unsupervised model for encoding and decoding fMRI activity in visual cortex," NeuroImage, 198: 125-136, 2019.
- Wen H, Shi J, Zhang Y, Lu K-H, Cao J, Liu Z, “Neural encoding and decoding with deep learning for dynamic natural vision,” Cerebral Cortex, 28(2): 4136-4160, 2018.
- Wen H, Han K, Shi J, Zhang Y, Culurciello E, Liu Z, “Deep predictive coding network for object recognition,” International Conference on Machine Learning (ICML), 2018.
- Lu K-H, Cao J, Oleson ST, Ward MP, Phillips RL, Powley TL, Liu Z, “Vagus nerve stimulation promotes gastric emptying by increasing pyloric opening measured with magnetic resonance imaging,” Neurogastroenterology and Motility, 30(10): e13380, 2018.
- He B, Sobrabpour A., Brown E., Liu Z, “Electrophysiological source imaging: a non-invasive window to brain dynamics,” Annual Review of Biomedical Engineering, 20: 171-196, 2018.
- Marussich L, Lu K-H, Wen H, Liu Z, "Mapping white-matter functional organization at rest and during naturalistic visual perception," NeuroImage, 146: 1128-1141, 2017.
- Wen H, Liu Z, “Broadband electrophysiological dynamics contribute to global resting-state fMRI signal,” Journal of Neuroscience, 36(22): 6030-6040, 2016.
- Wen H, Liu Z, "Separating fractal and oscillatory components in the power spectrum of neurophysiological signal," Brain Topography, 29(1): 13-26, 2016.