Deep reinforcement learning; Robot interaction perception and control; Automated machine learning techniques.

2013.09--2018.07 Ph.D., Institute of Automation, Chinese Academy of Sciences

2009.09--2013.07 B. S., Harbin Engineering University

[1].  Zixiang Ding, Yaran Chen, Nannan Li, Dongbin Zhao*, “BNAS-v2: memory-efficient and performance-collapse-prevented broad neural architecture search,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022,DOI: 10.1109/TSMC.2022.3143201

[2].  Yaran Chen, Ruiyuan Gao, Fenggang Liu, Dongbin Zhao*, “ModuleNet: knowledge-inherited neural architecture search,” IEEE Transactions on Cybernetics, DOI 10.1109/TCYB.2021.3078573. (SCI Q1, IF 11.448)

[3].  Haoran Li, Yaran Chen, Qichao Zhang, Dongbin Zhao, “BiFNet: bidirectional fusion network for road segmentation,” IEEE Transactions on Cybernetics, DOI 10.1109/TCYB.2021.3105488. (SCI Q1, IF 11.448)

[4].  Zixiang Ding, Yaran Chen, Nannan Li, Dongbin Zhao*, Z. Q. Sun, P. C. L. Chen, “BNAS: neural architecture search using broad scalable architecture,” IEEE Transactions on Neural Networks and Learning Systems, 2021, DOI 10.1109/TNNLS.2021.3067028. (SCI Q1, IF 10.451)

[5].  Nannan Li, Yu Pan, Yaran Chen*, Zixiang Ding, Dongbin Zhao, Zenglin Xu, “Heuristic rank selection with progressively searching tensor ring network,” Complex & Intelligent Systems, 2021, DOI: 10.1007/s40747-021-00308-x. (SCI Q2, IF 4.927)

[6].  Yi Lu, Yaran Chen, Dongbin Zhao*, Bao Liu, Zhichao Lai, Jianxin Chen, “CNN-G: convolutional neural network combined with graph for image segmentation with theoretical analysis,” IEEE Transactions on Cognitive and Developmental Systems, vol. 13, no. 3, pp. 631 – 644, Sept. 2021. (热点论文) (SCI Q3, IF 2.98/2019)

[7].  Yi Lu, Yaran Chen, Dongbin Zhao*, Dong Li, “Graph neural network-based inference in a Markov network for visual navigation,” Neurocomputing, vol. 421, pp. 140-150, 2021. DOI: 10.1016/j.neucom.2020.07.091 (SCI Q2, IF 5.19/2019).

[8].  Yaran Chen, Haoran Li, Ruiyuan Gao, Dongbin Zhao*, “Boost 3D object detection via point clouds segmentation and fused 3D GIoU-L1 loss,” IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TG.2020.3022698. (SCI Q1, IF 8.793)

[9].  Xiaodong Zhao, Yaran Chen*, Jin Guo and Dongbin Zhao, “A spatial-temporal LSTM model for human trajectory prediction,” IEEE/CAA Journal of Automatica Sinica, vol. 7, no. 4, pp. 965-974, July 2020. DOI: 10.1109/JAS.2020.1003228. (SCI Q2 IF 5.13)

[10]. Dong Li, Dongbin Zhao, Qichao Zhang, Yaran Chen, Reinforcement learning and deep learning based lateral control for autonomous driving, IEEE Computational Intelligence Magazine, vol. 14, no. 2, pp. 83 – 98, 2019.

[11]. Yaran Chen, Dongbin Zhao*, Le Lv, Qichao Zhang, “Multi-task learning for dangerous object detection in autonomous driving”, Information Sciences, vol. 432, pp. 559-571, 2018. DOI: 10.1016/j.ins.2017.08.035.

[12]. Dongbin Zhao , Yaran Chen, Le Lv, “Deep reinforcement learning with visual attention for vehicle classification,” IEEE Transactions on Cognitive and Developmental Systems, vol. 9, no. 4, pp. 356-367, 2017. (Outstanding Paper Award)

[13]. Xin Liu, Zixiang Ding, Nannan Li, Yaran Chen, Dongbin Zhao, “EGCN: ensemble graph convolutional network for neural architecture performance prediction,” 8th IEEE International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS), Dec. 11-12, 2021, Beijing, China.

[14]. Zhisong Zhang, Yaran Chen, Haoran Li and Qichao Zhang, “IA-CNN: A generalised interpretable convolutional neural network with attention mechanism,” IEEE/INNS International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, July 18 -22, 2021.

[15]. Junwen Chen, Yi Lu, Yaran Chen, Dongbin Zhao, Zhonghua Pang, “ContourRend: a segmentation method for improving contours by rendering,” M. Han et al. (Eds.): ISNN 2020, LNCS 12557, pp. 251–260, 2020.

[16]. Zixiang Ding, Yaran Chen, Nannan Li, Dongbin Zhao, Device placement optimization for deep neural networks via one-shot model and reinforcement learning, Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI) – Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Canberra, Australia, Dec. 1 - 4, 2020.

[17]. Nannan Li, Yaran Chen, Zixiang Ding and Dongbin Zhao, “Shift-invariant convolutional network search,” The International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, July 19 -24, 2020.

[18]. Haoran Li, Qichao Zhang, Dongbin Zhao and Yaran Chen, “RailNet: an information aggregation network for rail track segmentation,” The International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, July 19 -24, 2020.

[19]. Zixiang Ding, Yaran Chen, Nannan Li and Dongbin Zhao, “Simplified space based neural architecture search,” Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI) – Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Xiamen, China, Dec.6 - 9, 2019

[20]. Nannan Li, Yaran Chen Zixiang Ding Dongbin Zhao, “Multi-objective neural architecture search for light-weight model,” Chinese Automation Congress, Hangzhou, Nov. 22-24, 2019, accepted.

[21]. Yaran Chen, Dongbin Zhao, “Deep Kalman filter with optical flow for multiple object tracking,” IEEE International Conference on Systems, Man and Cybernetics, Bari, Italy, Oct. 6-9, 2019.

[22]. Hao Su, Yaran Chen, Shiwen Tong and Dongbin Zhao, “Real-time multiple object tracking based on optical flow,” The 9th International Conference on Information Science and Technology (ICIST), Hulunbuir, Inner Mongolia, China during August 2-5, 2019.

[23]. Junjie Wang, Qichao Zhang, Dongbin Zhao and Yaran Chen, “Lane change decision-making through deep reinforcement learning with rule-based constraints,” The International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 14 -19, 2019.

[24]. Yi Lu, Yaran Chen, Dongbin Zhao, Jianxin Chen, “Graph-FCN for image semantic segmentation,” In: Lu H., Tang H., Wang Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science, vol 11554, pp. 97-105, Springer, Cham

[25]. Haoran Li, Xiaolei Zhou, Yaran Chen, Dongbin Zhao, “Comparison of 3D object detection based on LiDAR point cloud,” IEEE Data Driven Control and Learning Systems Conference (DDCLS), Dali, China, May 25-27, 2019.

[26]. Yi Lu, Yaran Chen, Dongbin Zhao, “Hybrid deep learning based moving object detection via motion prediction,” Chinese Automation Congress (CAC 2018), Xi’an, China, Nov. 30-Dec.2, 2018, pp. 1862-1867.

[27]. Haoran Li, Dongbin Zhao, Yaran Chen, Qichao Zhang, “An efficient network for lane segmentation,” International Conference on Cognitive Systems and Information Processing (ICCSIP 2018), Beijing, China, Nov.29 - 31, 2018.

[28]. Yaran Chen, Dongbin Zhao, Haoran Li, Dong Li and Ping Guo, “A temporal-based deep learning method for multiple objects detection in autonomous driving,” The International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, July 8 – 13, 2018.

[29]. Dong Li, Dongbin Zhao, Yaran Chen and Qichao Zhang, “DeepSign: deep learning based rraffic sign recognition,” The International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, July 8 – 13, 2018. (Best Paper Award Final List).

[30]. Yaran Chen, Dongbin Zhao and Haoran Li, Deep kalman filter with optical flow for multiple object tracking, IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2019), 06-09 October Bari, Italy, 2019.

[31]. Yaran Chen, Dongbin Zhao, “Multi-task learning with Cartesian product-based multi-objective combination for dangerous object detection”, F. Cong et al. (Eds.): ISNN 2017, Part I, LNCS 10261, pp. 28–35, 2017.

[32]. Yaran Chen, Dongbin Zhao, Le Lv, Chengdong Li, “A visual attention based convolutional neural network for image classification,” Proceedings of the 12th World Congress on Intelligent Control and Automation (WCICA 2016), Guilin, China, July 12-15, 2016, pp.764-769. (Steve and Rosalind Hsia Best Biomedical Paper Award List)

[33]. Dongbin Zhao, Yuanheng Zhu, Le Lv, Yaran Chen and Qichao Zhang ‘Convolutional Fitted Q Iteration For Vision-Based Control Problems’; IJCNN 2016.(EI)

[34]. Dongbin Zhao, Le Lv, Yaran Chen, and Yuanheng Zhu. ‘Winner-Take-All Autoencoder Based Image Clustering’; The 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016) .(EI)

Deep Learning

Deep Reinforcement Learning

Computer Vision

Feature Representation

Embedded AI

1. 2020 DJI ICRA RoboMaster Artificial Intelligence Challenge - Sensing Champion
2. 2020 DJI ICRA RoboMaster Artificial Intelligence Challenge - Planing Champion
3. 2020 DJI ICRA RoboMaster Artificial Intelligence Challenge - Desicion Champion
4. China AI+ Innovation and Entrepreneurship Competition-The First Prize
5. China Smart Car Future Challenge Offline test - Pedestrian monitoring Champion 
6. China Smart Car Future Challenge Offline test - Vehicle distance monitoring Champion 
7. China Smart Car Future Challenge Offline test - Traffic signal recognition Third place  
8. 2020  IEEE Transactions on Cognitive and Development Systems - Outstanding Paper Award
9. 2022 IEEE Data Driven Control and Learning Systems Conference- Best Paper Finalist
10. 2018 IEEE International Joint Conference on NeuralNetworks- Best Paper Finalist
11. 2016 World Congress on Intelligent Control and Automation- Best Paper Finalist