个人简介
陈岑，博士，华南理工大学未来技术学院教授，博导，入选国家级高层次青年人才，广州创新创业青年拔尖人才。研究方向：面向大数据和人工智能的高效能计算、并行与分布式计算。已累计在权威学术期刊和会议上发表论文60余篇。其中一作或通讯作者论文43篇，包括IEEE& ACM期刊或CCF A类期刊论文23篇，CCF A类会议论文8篇，中科院SCI 1区期刊论文20篇，授权专利15项。获得湖南省优秀博士论文，湖南省计算机学会优秀博士论文，ACM 中国新星（Changsha Chapter）。因其在面向大数据和人工智能的高效能体系结构方面的成就，获得新加坡人工智能人才特殊津贴。近年来，主持或者参与国家自然科学基金面上项目、重点研发计划青年科学家项目、中国-新加坡自然科学基金国际(区域)合作与交流重点项目、华为EDA软件合作项目、新加坡国家人工智能项目、中国自然科学基金人工智能应急重点项目等。担任体系结构CCF A类期刊IEEE Transactions on Computers， Alexandria Engineering Journal （JCR Q1, IF = 6.8）编委, Neurocomputing、Journal of Parallel and Distributed Computing客座编辑。
每年招收博士生2名，硕士生2-4名，长期招收博士后。联系邮箱：chencen@scut.edu.cn
教育背景
2015. 09-2019.03, 湖南大学, 博士, 计算机科学与技术, 导师：李肯立
2011.09-2014.06，中山大学，硕士
2003.09-2007.06，华中科技大学，双学士
工作经历
2023.03 至今，华南理工大学未来技术学院，教授
2019.04 至 2023.03，新加坡科技研究院，资讯与通信研究所，高级别研究员（Research Scientist III）
2010.07 至 2013.07，普联技术有限公司，路由器研发，工程师
2008.04 至 2010.07，华为技术有限公司，网络产品线，工程师
2007.07 至 2008.04，金蝶软件（中国）有限公司，K3事业部，工程师
承担项目
(1)国家自然科学基金面上项目，“面向三维视觉的高效能智能计算关键技术研究”，2024/09/01 - 2028/12/31，在研，主持
(2)国家重点研发计划青年科学家项目，“以神经形态计算为突破口的可重构纳米电子器件研究” 2024/12 - 2027/11，在研，任务负责人
(3)CCF-飞腾基金项目面向Transformer智能模型的轻量化算法与体系结构协同优化研究 ， 2024/01/01 - 2024/12/31，在研，主持
(4)中国人工智能学会-昇思MindSpore学术基金，面向动态shape的图算融合性能加速， 2024/01/01 - 2024/12/31在研，主持
(5)广东省基础与应用基础研究基金自然科学基金面上项目，面向多模态边缘智能的高效能算法与体系结构协同设计，2024/01/01 - 2025/12/31, 在研，主持
(6)国自科国际合作与交流项目(No. 61661146006)：“面向列车故障监测的深度学习模型及其异构并行技术研究”，2017.01-2020.12，新加坡联合主持人，排名第二
(7)华为海思EDA软件合作项目, 面向芯片验证的“超大规模多目标切分与调度算法” ,时间：2020.11-2021.11, 联合主持人，排名第二
(8)国自科人工智能应急项目(No. 61751204)：“面向大规模多模态机器学习的异构众核并行处理方法与平台”，2018.01-2020.12，参与
所授课程
《并行程序设计与分布式计算》
标志性成果
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 (体系结构顶会，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 (体系结构顶会，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. (体系结构顶会，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)
