• MEng: 1) Electronic Information

• MS：1)Intelligent Science and Technology

• Ph.D: 1) Electronic Information; 2) Intelligent Science and Technology;

Chen Cen, Ph.D., is a professor and doctoral supervisor at the Future Technology College of South China University of Technology. He has been selected as a national high-level young talent and a top-notch young talent for innovation and entrepreneurship in Guangzhou. Research directions: High-performance computing, parallel and distributed computing for big data and artificial intelligence. More than 60 papers have been published in authoritative academic journals and conferences. Among them, 43 papers were published as the first author or corresponding author, including 23 papers in IEEE& ACM journals or CCF Class A journals, 8 papers in CCF Class A conferences, and 20 papers in SCI Zone 1 journals of the Chinese Academy of Sciences. 15 patents were authorized. Received the Excellent Doctoral Dissertation Award of Hunan Province, the Excellent Doctoral Dissertation Award of Hunan Computer Society, and the ACM China Rising Star (Changsha Chapter). Due to its achievements in high-performance architectures for big data and artificial intelligence, it has received the Singapore Artificial Intelligence Talent Special Allowance. In recent years, I have led or participated in projects such as the National Natural Science Foundation of China's general projects, the Key Research and Development Program for Young Scientists, the China-Singapore Natural Science Foundation of China's Key International (Regional) Cooperation and Exchange projects, the Huawei EDA Software cooperation Project, the Singapore National Artificial Intelligence Project, and the China Natural Science Foundation of China's emergency Key Project on artificial intelligence. Served in the CCF Class A journal IEEE Transactions on Computers for architecture Editorial Board Member of Alexandria Engineering Journal (JCR Q1, IF = 6.8), Guest Editor of Neurocomputing, Journal of Parallel and Distributed Computing.

• Artificial intelligence, big data, architecture, parallel and distributed computing

• Cen Chen, Xiaofeng Zou, Hongen Shao, Yangfan Li, Kenli Li, Point Cloud Acceleration by Exploiting Geometric Similarity, MICRO 2023 International Symposium on Micro architecture, 2023 (CCF A Conference)  

• Cen Chen, Kenli Li, Xiaofeng, Zou, Yangfan Li, “ReGNN: A Redundancy-Eliminated Graph Neural Networks Accelerator”, The 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA-28) , 2022,IEEE, 2022: 429-443 (CCF A Conference)

• Cen Chen, Kenli Li, Yangfan Li, Xiaofeng, Zou, “DyGNN: Algorithm and Architecture Support of Dynamic Pruning for Graph Neural Networks”, 58th Design AutomationConference (DAC), IEEE, 2021: 1201-1206. (CCF A Conference)

• Cen Chen, Kenli Li, Sin G. Teo, Xiaofeng Zou, Xulei Yang, Ramaseshan C. Vijay and Zeng Zeng, “Gated Residual Recurrent Graph Neural Networks for Traffic Prediction”, 33th AAAI Conference on Artificial Intelligence (AAAI-19), 33(01): 485-492. (CCF A Conference)

• Huiping Zhuang，Run He，Kai Tong，Ziqian Zeng，Cen Chen，Zhiping Lin , DS-AL: A Dual-Stream Analytic Learning for Exemplar-Free Class-Incremental Learning, 38th AAAI Conference on Artificial Intelligence (AAAI-24) (Accepted) (CCF A Conference)

• Ziqian Zeng , Yihuai Hong, Hongliang Dai, Huiping Zhuang, Cen Chen, ConsistentEE: A Consistent and Hardness-Guided Early Exiting Method for Accelerating Language Models Inference,38th AAAI Conference on Artificial Intelligence (AAAI-24) (Accepted) (CCF A Conference)

• Mi Li, Cen Chen*, Xulei Yang, Joey Tianyi Zhou, Tao Zhang, and Yangfan Li，Towards Communication-efficient Digital Twin via AI-powered Transmission and Reconstruction, IEEE Journal on Selected Areas in Communications (JSAC), 2023 (CCF A Journal, IF=16.4, JCR Q1)

• Cen Chen, Kenli Li, A. Ouyang, Z. Zeng and K. Q. Li, “GFlink: An in-memory computing architecture on heterogeneous CPU-GPU clusters for big data,” IEEE Transactions on Parallel and Distributed Systems, 2018, 29(6): 1275-1288. (CCF A Journal)

• Cen Chen, Kenli Li, A. Ouyang, and K. Q. Li, “FlinkCL: An OpenCL-based In-Memory Computing Architecture on Heterogeneous CPU-GPU Clusters for Big Data,” IEEE Transactions on Computers, 2018, 67(12): 1765-1779., (CCF A Journal)

• Xiaofeng Zou, Cen Chen, Peiying Lin, Luochuan Zhang, Yanwu Xu, Wenjie Zhang, Scalable Heterogeneous Scheduling based Model Parallelism for Real-Time Inference of Large-Scale Deep Neural Networks, IEEE Transactions on Emerging Topics in Computational Intelligence(TETCI) (Accepted)

• Cen Chen, Kenli Li, Zhongyao Cheng, Wei Wei, Qi Tian, Zeng Zeng, “Hierarchical Semantic Graph Reasoning for Train Component Detection”, IEEE Transactions on Neural Networks and Learning Systems, 2021, 33(9): 4502-4514. (JCR Q1)

• Cen Chen, Xiaofeng Zou, Zeng Zeng, Zhongyao Cheng, CH Steven, “Exploring Structural Knowledge for Automated Visual Inspection of Moving Trains”, IEEE Transactions on Cybernetics, 2020, 52(2): 1233-1246. (JCR Q1)

• Cen Chen, K. Li, A. Ouyang, Z. Tang and K. Q. Li, “GPU-Accelerated Parallel Hierarchical Extreme Learning Machine on Flink for Big Data”， IEEE Transactions on Systems Man & Cybernetics Systems: Systems, 2017, 47(10):2740-2753, (JCR Q1)

• Cen Chen, Kenli Li, Wei Wei, Joey Tianyi Zhou, Zeng Zeng, “Hierarchical Graph Neural Networks for Few-Shot Learning”, IEEE Transactions on Circuits and Systems for Video Technology, 2021, 32(1): 240-252., (JCR Q1)     

• Cen Chen, Kenli Li, Cheng Zhongyao, Francesco Piccialli, Steven CH Hoi, Zeng Zeng, “A Hybrid Deep Learning based Framework for Component Defect Detection of Moving Trains”, IEEE Transactions on Intelligent Transportation Systems, 2020, 23(4): 3268-3280. (JCR Q1)

• Cen Chen, Kenli Li, Sin G Teo, Xiaofeng Zou, Keqin Li, Zeng Zeng, “Citywide Traffic Flow Prediction based on Multiple Gated Spatio-temporal Convolutional Neural Networks”, ACM Transactions on Knowledge Discovery from Data (TKDD), 2020, 14(4): 1-23. (CCF B Journal)

• Cen Chen, Kenli Li, Sin G. Teo, Guizi Chen, Xiaofeng Zou, Xulei Yang, Ramaseshan C. Vijay, Jiashi Feng and Zeng Zeng, “Exploiting Spatio-Temporal Correlations with Multiple 3D Convolutional Neural Networks for Citywide Vehicle Flow Prediction”, IEEE International Conference on Data Mining (ICDM), 2018: 893-898.,  (CCF B Conference)

• Cen Chen, K. Li, A. Ouyang, and K. Q. Li, “A Parallel Approximate SS-ELM Algorithm based on MapReduce for Large-Scale Datasets”, Journal of Parallel and Distributed Computing，2017，208：85-94, ( JCR Q1) 

• Cen Chen, K. Li, A. Ouyang, Z. Tang, and K. Q. Li, “GFlink: An in-memory computing architecture on heterogeneous CPU-GPU clusters for big data”， Parallel Processing (ICPP), 2016 45th International Conference on. IEEE, 2016: 542-551, (CCF B Conference)

• Ming Yan, Cen Chen*, Jiawei Du, Xi Peng, Joey Tianyi Zhou, Zeng Zeng，“Memory-assistant Collaborative Language Understanding for Artificial Intelligence of Things”，IEEE Transactions on Industrial Informatics, 2021, 18(5): 3349-3357.,  (JCR Q1)

• Chi Zhang, Liangli Zhen, Joey Tianyi Zhou, Cen Chen*, “Distributed Monitoring for Energy Infrastructures: A Two-Tier Analysis Over Wireless Networks”, IEEE Wireless Communications, 2021, 28(6): 13-18.  (JCR Q1)     

• Z Zhao, Z Zeng, K Xu, Cen Chen*, C Guan, “DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation”, IEEE Journal of Biomedical and Health Informatics, 2021, 25(10): 3744-3751., (JCR Q1)

• Jianxi Yang, Likai Zhang, Cen Chen*, Yangfan Li, Ren Li, Guiping Wang, Shixin Jiang , Zeng Zeng, “A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection”,  Information Sciences, 2020, 540: 117-130.,  (JCR Q1)

• Yangfan Li, Cen Chen*, Kenli Li,“Attention-Aware Encoder-Decoder Graph Neural Networks for Heterogeneous Graph of Things”, IEEE Transactions on Industrial Informatics, 2020, 17(4): 2890-2898., (JCR Q1)

• Xiaofeng Zou, Kenli Li, Cen Chen*, “Multi-Level Attention based U-Shape Graph Neural Network for Point Clouds Learning”,  IEEE Transactions on Industrial Informatics, 2020, 18(1): 448-456.，(JCR Q1)

• Chigang Xing, Yangfan Li, Cen Chen*, “Determinantal Point Process-based New Radio Unlicensed Link Scheduling for Multi-access Edge Computing”, World Wide Web: Internet and Web Information Systems (WWWJ), 2022, 25(5): 2215-2239. (JCR Q1)

• Zeng Zeng,  Ziyuan Zhao, Kaixin Xu, Cen Chen*, Yulan Wang, Wei Wei, Pierce KH Chow and Xiaoli Li,  “CoIn:    Correlation Induced Clustering for Cognition of High Dimensional Bioinformatics Data”, IEEE Journal of Biomedical And Health Informatics, 2022, (JCR Q1)

• Jing Liu, Pei Yang, Cen Chen*，“Intelligent Energy-Efficient Scheduling with Ant Colony Techniques for Heterogeneous Edge Computing，Journal of Parallel and Distributed Computing”，2023, 172: 84-96.，(JCR Q1)

• Yangfan Li, Cen Chen*, Weiquan Yan, Zhongyao Cheng, Hui Li Tanm, Wenjie Zhang. Cascade Graph Neural Networks for Few-shot Learning on Point Clouds[J]. IEEE Transactions on Intelligent Transportation Systems (TITS), 2023. (JCR Q1)