Yan Liu, Ph.D


Research Areas

Signal Processing, Image Processing, Artificial Intelligence


1. Set.2004-Jul. 2007   Ph.D in Signal and Information Processing, 
    Institute of Electronics, Chinese Academy of Sciences, Beijing.

2. Set.2001-Jul. 2004    M.S in Communication and Information System, 
    School of Information Science and Engineering, Shandong University, Jinan.

3. Set.1997-Jul. 2001    B.S in Electronic Information Science and Technology, 
    School of Information Science and Engineering, Shandong University, Jinan.


Work Experience

Dec. 2013-Jan. 2015  Visiting Scholar, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign.

Jul. 2007-present Associate Professor,  School of Computer and Control Engineering, University of Chinese Academy of Sciences.

Teaching Experience
1. Advanced Digital Signal Processing
2. Modern Signal Processing Theory and Method



  • Pulmonary Nodules Detection Assistant Platform: An Effective Computer Aided System for Early Pulmonary Nodules Detection in Physical Examination, Computer Methods and Programs in Biomedicine,2022, 217: 1-12.

  • Multi-resolution 3D-HOG Feature Learning Method for Alzheimer’s Disease Diagnosis, Computer Methods and Programs in Biomedicine, 2021, 214:1-8.

  • Shallow-Layers-Detection Ice Sounding Radar for Mapping of Polar Ice Sheets. IEEE Transactions on Geoscience and Remote Sensing, 2021, (99): 1-10.

  • Preliminary Investigation and Imaging Analysis of Early Lung Cancer Screening Among Petroleum Workers in North China, Cancer Investigation, 2021, 39(4): 321-332.

  • Efficient False Positive Reduction Method for Early Pulmonary Nodules Detection in Physical Examination, BIBM'2021.

  • Wavelet-based Multi-branch Convolutional Neural Network for Cross-individual ALS Disease Identification with EMG Signal, BIBM'2021.

  • Omics feature learning for cross individual ALS disease identification with EMG signal, BIBM'2021.

  • Analysis on Teeth Occlusion Distribution Based on Segmentation and Registration Algorithm, BIBM'2021.

  • Automated Classification of Alzheimer’s Disease and Mild Cognitive Impairment By Multi-scale Residual Neural Network in Hippocampus Subfields MR Images, RSNA’2021.

  • Automated Classification of Alzheimer’s Disease by Graph Convolutional network in Multi-modal MR Images, RSNA’2021.

  • Region-of-Interest Based Sparse Feature Learning Method for Alzheimer’s Disease Identification. Computer Methods and Programs in Biomedicine, 2020, 187: 1-10.

  • Gabor filter banks used for crevasse detection with Ground Penetrating Radar data, GPR’2020.

  • A Wrapper-based Feature Learning Method used for Alzheimer's disease Identification, ICSP2020.

  • Spatial Pyramid Based 3D Hog Feature Extraction for Alzheimers Disease Identification, ICSP2020.

  • Ice Crevasse Detection with Ground Penetrating Radar using Faster R-CNN, ICSP2020.

  • Automatic Sleep Stage Classification using Marginal Hilbert Spectrum Features and a Convolutional Neural Network, EMBC2020.

  • Comparison and Analyzation of Different Feature Parameters for Alzheimer’s disease Identification, EMBC'2019.

  • Tracing the Layer Boundary of the Ice Sheet from Radio-Echo Sounding Data, GPR’2018.

  • Compartmental Gaussian Mixture Model used for Layer Detection in Radio-Echo Sounding Data, ICSP’2018.

  • An Automatic Classification of Alzheimer’s Disease Based on Structural MRI Data Compared with Voxel-Based Morphometry Method. ISMRM’2018.

  • Automated Classification of Alzheimer’s Disease by Interregional Correlation Matrix in Structural MR Images. RSNA’2018.

  • Compartmental Sparse Feature Selection Method for Alzheimer’s disease Identification. EMBC’2017.  

  • Elastic Net based sparse feature learning and classification for Alzheimer’s disease identification. EMBC’2017.

  • Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and B0 Field Inhomogeneity, IEEE Transactions on Biomedical Engineering, 2016, vol.63, no.4, pp: 841-849.

Research Interests

1. Signal Processing
2. Image Processing
3. Artificial Intelligence