CHEN Cen

Academic Title: Professor

Research Interests: Artificial intelligence, Big data, Computer architecture, Parallel, Distributed computing

Biography

Chen Cen, Ph.D., is a Professor and Doctoral Supervisor at the School of Future Technology, South China University of Technology (SCUT). He has been selected as a National-Level High-Level Young Talent and a Top Young Talent for Innovation and Entrepreneurship in Guangzhou. His research focuses on High-Performance Computing for Big Data and Artificial Intelligence, and Parallel and Distributed Computing. He has cumulatively published over 60 papers in authoritative academic journals and conferences. Among these, there are 43 first- or corresponding-author papers, including 23 papers in IEEE & ACM or CCF A-list journals, 8 papers in CCF A-list conferences, and 20 papers in Chinese Academy of Sciences SCI Q1 journals. He also holds 15 authorized patents. He received the Outstanding Doctoral Dissertation Award of Hunan Province, the Outstanding Doctoral Dissertation Award of the Hunan Computer Federation, and the ACM China Rising Star (Changsha Chapter). Due to his achievements in high-performance architecture for Big Data and AI, he was awarded the Singapore AI Talent Special Allowance. In recent years, he has led or participated in projects including the National Natural Science Foundation of China (General Program), National Key R&D Program Young Scientist Project, China-Singapore NSFC Key International (Regional) Cooperation and Exchange Project, Huawei EDA Software Cooperation Project, Singapore National AI Project, and China NSFC Emergency Key Project on AI. He serves on the Editorial Board of the CCF A-list architecture journal IEEE Transactions on Computers and Alexandria Engineering Journal (JCR Q1, IF = 6.8). He is also a Guest Editor for Neurocomputing and Journal of Parallel and Distributed Computing. He recruits 2 Ph.D. students and 2-4 Master's students annually. Long-term recruitment of Postdoctoral Fellows.

Contact: chencen@scut.edu.cn

Personal Website

https://www2.scut.edu.cn/bioinformatics/sysPIjs/list.htm

Education

2015.09-2019.03, Ph.D., Computer Science and Technology, Hunan University, China

2011.09-2014.06, M.S., Sun Yat-sen University, China
2003.09-2007.06, Dual B.S., Huazhong University of Science and Technology, China

Work Experience

2023.03–Present, Professor, School of Future Technology, SCUT
2019.04–2023.03, Research Scientist III, Institute for Infocomm Research (I²R), Agency for Science, Technology and Research (A*STAR), Singapore
2010.07–2013.07, Engineer, Router R&D, TP-Link Technologies Co., Ltd.
2008.04–2010.07, Engineer, Network Product Line, Huawei Technologies Co., Ltd.
2007.07–2008.04, Engineer, K3 Business Unit, Kingdee Software (China) Co., Ltd.

Courses Taught

Parallel Programming and Distributed Computing

Research Projects

[1] National Natural Science Foundation of China (General Program), Research on Key Technologies of High-Performance Intelligent Computing for 3D Vision. 2024/09/01 - 2028/12/31, Host, Ongoing.
[2] National Key R&D Program Young Scientist Project, Research on Reconfigurable Nanoelectronic Devices with Neuromorphic Computing as a Breakthrough. 2024/12 - 2027/11, Task Leader, Ongoing.
[3] CCF-FeiTeng Fund Project, Collaborative Optimization of Lightweight Algorithms and Architecture for Transformer Intelligent Models. 2024/01/01 - 2024/12/31, Host, Ongoing.
[4] China AI Society-MindSpore Academic Fund, Performance Acceleration of Graph-Operator Fusion for Dynamic Shape. 2024/01/01 - 2024/12/31, Host, Ongoing.
[5] CCF-Baidu Songguo Fund Project, Research on General Hardware Adaptation Technology for Compiler Optimization. 2025/01/01-2026/01/01, Host, Ongoing.
[6] University Joint Cooperation Agreement, Application of Knowledge Transfer and Large Language Models in Personalized Search. 2023/12/31- 2025/01/01, Host, Ongoing.
[7] University Joint Cooperation Agreement, Research on Multimodal Large Model Content Understanding in E-commerce Live Streaming Operations. 2025/01/01-2025/12/31, Host, Ongoing.
[8] Guangdong Basic and Applied Research Foundation Natural Science Foundation General Program, Co-Design of High-Performance Algorithms and Architecture for Multimodal Edge Intelligence. 2024/01/01 - 2025/12/31, Host, Ongoing.
[9] NSFC International Cooperation and Exchange Program (No. 61661146006), Deep Learning Models and Heterogeneous Parallel Technology for Train Fault Monitoring. 2017.01-2020.12, Co-Host (Rank 2), Completed.
[10] Huawei HiSilicon EDA Software Cooperation Project, Ultra-Large-Scale Multi-Objective Partitioning and Scheduling Algorithm for Chip Verification. 2020.11-2021.11, Co-Host (Rank 2), Completed.
[11] NSFC Emergency Key Project on Artificial Intelligence (No. 61751204), Heterogeneous Many-Core Parallel Processing Methods and Platform for Large-Scale Multi-Modal Machine Learning. 2018.01-2020.12, Participant, Completed.

Selected Publications

[1] Y. Hu, E. Guo, Z. Xie, X. Liu, and H. Cai*. Robust Multi-view Clustering through Partition Integration on Stiefel Manifold. IEEE Transactions on Knowledge and Data Engineering (2023). DOI: 10.1109/TKDE.2023.3253244.(CAS Tier 2, JCR Q1, IF: 8.9)

[2] H. Cai, B. Zhang, J. Li, B. Hu, and J. Chen. Unsupervised Dual Hashing Coding (UDC) on Semantic-wise Tagging and Sample-wise Content for Cross-modal Retrieval. IEEE Transactions on Multimedia (2023).(CAS Tier 1, JCR Q1, IF: 7.3)

[3] B. Zhang, Y. Zhang, J. Li, J. Chen, T. Akutsu, Y. Cheung, and H. Cai*. Unsupervised Dual Deep Hashing with Semantic-Index and Content-Code for Cross-Modal Retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023). (CAS Tier 1, JCR Q1, IF: 23.6)

[4] H. Cai, L. Zhu, Y. Liao, J. Song*. Improving cancer survival prediction via graph convolutional neural networks learning on protein-protein interaction networks. IEEE Journal of Biomedical and Health Informatics, (2023).(CAS Tier 1, JCR Q1, IF: 7.7)

[5] M. Lin, X. Zhang, R. You, Y. Liu, H. Cai, et. al, T. Liu, M. Chen. Evolutionary route of nasopharyngeal carcinoma metastasis and its clinical significance. Nature Communications 14.1 (2023): 610.(CAS Tier 1, JCR Q1, IF: 16.6)

[6] G Tao, H Li, J Huang, C Han, J Chen, G Ruan, W Huang, Y Hu, T Dan, et. al, H. Cai*. SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance. Medical Image Analysis 78 (2022): 102381.(CAS Tier 1, JCR Q1, IF: 10.9)

[7] J. Li, J. Chen, F. Qi, T. Dan, W. Weng, B. Zhang, H. Yuan, and H. Cai*. Two-dimensional unsupervised feature selection via sparse feature filter. IEEE Transactions on Cybernetics (2022). DOI: 10.1109/TCYB.2022.3162908.(CAS Tier 1, JCR Q1, IF: 11.8)

[8] Y. Li, T. Dan, H. Li, J. Chen, H. Peng, L. Liu, H. Cai*. NPCNet: jointly segment primary nasopharyngeal carcinoma tumors and metastatic lymph nodes in MR images. IEEE Transactions on Medical Imaging 41.7 (2022): 1639-1650.(CAS Tier 1, JCR Q1, IF: 10.6)

[9] H. Peng, Y. Hu, J. Chen, H. Wang, Y. Li, and H. Cai*. Integrating tensor similarity to enhance clustering performance. IEEE Transactions on Pattern Analysis and Machine Intelligence 44.5 (2020): 2582-2593.(CAS Tier 1, JCR Q1, IF: 23.6)

Selected Invited Talks

1.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)
2.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)
3.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)
4.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)
5.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)
6.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)
7.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)
8.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)
9.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)
10.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)
11.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)
12.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)
13.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)
14.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)
15.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)
16.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)
17.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)
18.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)
19.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)
20.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)
21.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)
22.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)
23.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)
24.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)
25.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)
26.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)
27.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)
28.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)
29.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)