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Li He--Research Associate Professor

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Dr. Li He is currently a Research Associate Professor in the Department of Electronic and Electrical Engineering at Southern University of Science and Technology (SUSTech). Prior to joining SUSTech, he was an Associate Professor in the School of Electromechanical Engineering, Guangdong University of Technology. He is a recipient of the Pearl River Talent Recruitment Program of Guangdong, and Shenzhen Peacock Plan (Type C). He is an Associate Editor/ Guest Managing Editor of Computers & Electrical Engineering, and an Associate Editor of IEEE Access. He served as a committee member for ICRA, ROBIO and WRC SARA. Dr. He has more than 30 publications on high-rank venues such as TIP, TCYB, PR, IROS and ICRA. He has individually chaired more than 6 grants of over 3 million RMB, including 2 National Grants. Dr. He’s research interests include machine learning, computer vision, large-scale data clustering, LiDAR navigation and SLAM.

Education

2008-2014, Ph.D., Dept. of Automation, Northwestern Polytechnical University, China

2010-2011, Joint Ph.D., Dept. of Computing Science, University of Alberta, Canada

2008-2014, M.S., Dept. of Automation, Northwestern Polytechnical University, China

2008-2014, B.S., Dept. of Automation, Northwestern Polytechnical University, China

Working Experiences

2021-present, Research Associate Professor, Dept. of Electrical and Electronic Engineering, Southern University of Science and Technology, China

2018-2021, Associate Professor, School of Electromechanical Engineering, Guangdong University of Technology, China

2017-2018, Assistant Professor, School of Electromechanical Engineering, Guangdong University of Technology, China

2014-2017, Postdoctoral Fellow, Dept. of Computing Science, University of Alberta, Canada

Research Introduction

Machine Learning

Computer Vision

Large-scale Data Clustering

LiDAR Navigation

SLAM

Awards & Honors

Recipient of The Pearl River Talent Recruitment Program of Guangdong, China.

Shenzhen Peacock Plan (Type C), China

Member of Innovative and Enterprising Team under The Sailing Program of Guangdong, China

Papers

Large-scale Data Clustering

1.  Li He, Nilanjan Ray, Yisheng Guan and Hong Zhang. Fast Large-Scale Spectral Clustering via Explicit Feature Mapping. IEEE Transactions on Cybernetics, Vol. 49, Issue 3, March 2019, pp. 1058-1071.

2. Li Heand Hong Zhang. Kernel K-means Sampling for Nystrom Approximation. IEEE Transactions on Image Processing, Volume 27, Issue 5, May 2018, pp. 2108-2120.

3. Li He, Nilanjan Ray and Hong Zhang. Error Bound of Nystrom-approximated NCut Eigenvectors and Its Application to Training Size Selection. Neurocomputing, 2017, Vol. 239, May: 130-142.

4. Li Heand Hong Zhang. Iterative Ensemble Normalized Cuts. Pattern Recognition, 2016, Vol. 52, April: 274-286.

 

SLAM

1. Li He, Xiaolong Wang, and Hong Zhang. M2DP: A novel 3D point cloud descriptor and its application in loop closure detection. In Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, pp.231-237. IEEE, 2016.

2. Weinan Chen, Lei Zhu, Xubin Lin, Yisheng Guan, Li Heand Hong Zhang. Dynamic Strategy of Keyframe Selection with PD Controller for VSLAM Systems. IEEE/ASME Transactions on Mechatronics, to appear.

3. Weinan Chen, Lei Zhu, Chaoqun Wang, Li Heand Max Q.-H. Meng. CEB-Map: Visual Localization Error Prediction for Safe Navigation. IEEE Sensors Journal, vol. 21, no. 10, pp. 11769-11780, 15 May15, 2021.

4. Wen JM, He L*and Zhu FM. Swarm Robotics Control and Communications: Imminent Challenges for Next Generation Smart Logistics. IEEE Communications Magazine, 2018, 56(7): 102-107.

5. Xubin Lin, Yirui Yang, Li He, Weinan Chen, Yisheng Guan, Hong Zhang. Robust Improvement in 3D Object Landmark Inference for Semantic Mapping. ICRA 2021.

6. Zhuang Dai, Xinghong Huang, Weinan Chen, Chuangbing Chen, Li He, Shuhuan Wen and Hong Zhang. Keypoint Description by Descriptor Fusion Using Autoencoders. ICRA 2020.

6. Zhuang Dai, Xinghong Huang, Weinan Chen, Li Heand Hong Zhang. A Comparison of CNN-Based and Hand-Crafted Keypoint Descriptors. ICRA 2019.

7. Xinghong Huang, Zhuang Dai, Weinan Chen, Li He and Hong Zhang. Improving Keypoint Matching Using a Landmark-Based Image Representation. ICRA 2019.

8. Lin, W. Chen, Li He, et al. Improving Robustness of Monocular VT&R System with Multiple Hypothesis, ROBIO 2017. (ROBIO 2017 T. J. Tarn Best Paper Awards Finalist)

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