General

Yan Liu, Ph.D

Email:
yanliu@ucas.ac.cn

Research Areas

Signal Processing, Image Processing, Artificial Intelligence
 

Education

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.

Experience

   
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

Publications

   
Papers

  • 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