个人简介
程龙,博士,现为华北电力大学控制与计算机工程学院教授、博士生导师。他之前是爱尔兰国家数据分析研究中心访问教授、爱尔兰都柏林城市大学计算机学院助理教授、欧盟玛丽居里学者。主要研究方向是并行分布式计算、深度学习、云计算和大数据处理以及这些技术在流程挖掘与能源大数据上的应用。曾在华为德国,IBM都柏林研究院工作过,并且在德国德累斯顿工业大学和荷兰埃因霍温理工大学从事过博士后研究,具有多年一线大数据系统和算法设计、开发与优化经验, 于2018年获得欧盟资助个人科研最高奖项之一玛丽居里个人基金,并入选2023年斯坦福全球前2%顶尖科学家榜单。
程教授在并行分布式计算和大数据处理的权威期刊与会议比如TPDS、TON、TC、TSC、TCC、TNSM、TCAD、TASE、TVT、TSMC、T-ITS、IEEE Network、JPDC、HPCA、ICPP、CIKM、CCGrid和EuroPar上发表近100篇文章(含IEEE/ACM Transactions/Magazine/Journal 近40篇),并且长期为对应的期刊和会议审稿,同时也是IPDPS、ICPP、CCGrid和CLUSTER等知名国际会议的程序委员会成员。他于2007年本科毕业于哈尔滨工业大学,2010年硕士毕业于德国杜伊斯堡-艾森大学(硕士论文由华为德国公司资助),并于2014年获得爱尔兰国立大学-梅努斯的博士学位(由爱尔兰国家研究委员会全额博士奖学金资助)。目前是IEEE高级会员,IEEE Transactions on Consumer Electronics编委,SCI期刊Journal of Cloud Computing副主编(Co-Chair),IEEE TCE、FGCS、Applied Soft Computing、Computer Communications等权威期刊客座编辑,IEEE TPDS期刊Review Board成员,瑞士国家自然科学基金(SNSF)外国评审专家。
部分最新论文
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L. Cheng, L. Du, C. Liu, Y. Hu, F. Fang, T. Ward. Multi-modal fusion for business process prediction in call center scenarios, Information Fusion, 2024 (中科院一区)
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Q. Liu, Y. Huang, C. Jin, X. Zhou, Y. Mao, C. Catal, L. Cheng (通讯). Privacy and Integrity Protection for IoT Multimodal Data using Machine Learning and Blockchain, ACM Transactions on Multimedia Computing, Communications, and Applications, 2024 (CCF-B)
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X. Chen, Q. Yu, S. Dai, P. Sun, H. Tang, L. Cheng (通讯). Deep Reinforcement Learning for Efficient IoT Data Compression in Smart Railroad Management, IEEE Internet of Things Journal, 2024 (中科院一区)
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S. Li, J. Li, Y. Liang, H. Zhang, S. Wu, S. Wang, L. Cheng. TD-SAS: A Trust-Aware and Decentralized Speed Advisory System for Energy-Efficient Autonomous Vehicle Platoons, IEEE Transactions on Intelligent Vehicles, 2023 (中科院一区)
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C. Liu, Y. Wang, L. Wen, J. Cheng, L. Cheng, Q. Zeng. Discovering Hierarchical Multi-instance Business Processes from Event Logs, IEEE Transactions on Services Computing, 2023 (CCF-A)
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L. Cheng, Yue Wang, F. Cheng, C. Liu, Z. Zhao, Ying Wang. A Deep Reinforcement Learning-based Preemptive Approach for Cost-aware Cloud Job Scheduling, IEEE Transactions on Sustainable Computing, 2023 (中科院二区)
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J. Zhang, L. Cheng (通讯), C. Liu, Z. Zhao, Y. Mao. Cost-Aware Scheduling Systems for Real-Time Workflows in Cloud: An Approach based on Genetic Algorithm and Deep Reinforcement Learning, Expert Systems with Applications, 2023 (中科院一区)
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J. Guo, L. Cheng, S. Wang. CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement Learning, IEEE Transactions on Intelligent Transportation Systems, 2023 (中科院一区)
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L. Cheng, Y. Wang, R. Jhaveri, Q. Wang, Y. Mao. Towards Network-aware Query Execution Systems in Large Datacenters, IEEE Transactions on Network and Service Management, 2023 (中科院二区)
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H. Huang, X. Xue, C. Liu, Y. Wang, T. Luo, L. Cheng, H. Li, X. Li. Statistical Modeling of Soft Error Influence on Neural Networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023 (CCF-A)
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Z. Chen, J. Li, L. Cheng, X. Liu. Federated-WDCGAN: A Federated Smart Meter Data Sharing Framework for Privacy Preservation. Applied Energy, 2023 (中科院一区)
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J. Li, X. Tong, J. Liu, L. Cheng (通讯). An efficient Federated Learning System for Network Intrusion Detection. IEEE Systems Journal, 2023 (中科院二区)
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S. Li, J. Li, J. Pei, S. Wu, S. Wang, L. Cheng. Eco-CSAS: A Safe and Eco-friendly Speed Advisory System for Autonomous Vehicle Platoon using Consortium Blockchain, IEEE Transactions on Intelligent Transportation Systems, 2022 (中科院一区)
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L. Cheng, C. Liu, Q. Zeng. Optimal Alignments Between Large Event Logs and Process Models over Distributed Systems: An Approach Based on Petri Nets, Information Sciences, 2023 (中科院一区)
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Y. Xu, L. Cheng, X. Cai, X. Ma, W. Chen, L. Zhang. Y. Wang. Efficient Supernet Training Using Path Parallelism. Proc. 29th IEEE International Symposium on High-Performance Computer Architecture (HPCA 2023), Montreal, Canada, 2023 (CCF-A)
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Y. Mao, V. Sharma, W. Zheng, L. Cheng, Q. Guan, A. Li. Elastic Resource Management for Deep Learning Applications in a Container Cluster. IEEE Transactions on Cloud Computing, 2022 (中科院二区)
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J. Li, S. Li, L. Cheng (通讯), Q. Liu, J. Pei, S. Wang. BSAS: A Blockchain-based Trustworthy and Privacy-Preserving Speed Advisory System. IEEE Transactions on Vehicular Technology, 2022 (中科院二区)
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J. Li, Z. Chen, L. Cheng (通讯), X. Liu. Energy Data Generation with Wasserstein Deep Convolutional Generative Adversarial Networks. Energy, 2022 (中科院一区,ESI高被引论文)
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L. Cheng, A. Kalapgar, A. Jain, Y. Wang, Y. Qin, Y. Li, C. Liu. Cost-aware Real-time Job Scheduling for Hybrid Cloud using Deep Reinforcement Learning. Neural Computing and Applications, 2022 (中科院二区)
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C. Liu, H. Li, S. Zhang, L. Cheng, Q. Zeng. Cross-Department Collaborative Healthcare Process Model Discovery from Event Logs. IEEE Transactions on Automation Science and Engineering, 2022 (CCF-B).
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Y. Mao, W. Yan, Y. Song, Y. Zeng, M. Chen, L. Cheng, Q. Liu. Differentiate Quality of Experience Scheduling for Deep Learning Inferences with Docker Containers in the Cloud. IEEE Transactions on Cloud Computing, 2022 (中科院二区).
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Q. Liu, T. Xia, L. Cheng (通讯), M. Eijk, T. Ozcelebi, Y. Mao. Deep Reinforcement Learning for Load-Balancing Aware Network Control in IoT Edge Systems. IEEE Transactions on Parallel and Distributed Systems, 2022. (CCF-A).
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Y. Mao, Y. Fu, W. Zheng, L. Cheng, Q. Liu, D. Tao. Speculative Container Scheduling for Deep Learning Applications in a Kubernetes Cluster. IEEE Systems Journal, 2021 (中科院二区).
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Y. Huang, L. Cheng (通讯), L. Xue, C. Liu, Y. Li, J., T. Ward. Deep Adversarial Imitation Reinforcement Learning for QoS-aware Cloud Job Scheduling. IEEE Systems Journal, 2021 (中科院二区).
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王颖,刘聪,闻立杰,曾庆田,程龙. 一种分层多实例过程模型挖掘方法. 中国业务过程管理大会, 2021 (最佳学生论文奖,最具有企业应用价值奖).
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K. Zou, Y. Wang, L. Cheng, S. Qu, H. Li, X. Li. CAP: Communication-aware Automated Parallelization for Deep Learning Inference on CMP Architectures. IEEE Transactions on Computers, 2021 (CCF-A).
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Y. Wang, Y. He, L. Cheng, H. Li, X. Li. A Fast Precision Tuning Solution for Always-On DNN Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021 (CCF-A).
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D. Xu, M. He, C. Liu, Y. Wang, L. Cheng, H. Li, X. Li, K. Cheng. R2F: A Remote Retraining Framework for AIoT Processors with Computing Errors. IEEE Transactions on Very Large Scale Integration Systems, 2021 (CCF-B).
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C. Liu, L. Cheng, Q. Zeng, L. Wen. Formal Modeling and Discovery of Hierarchical Business Processes: A Petri Net based Approach. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2022 (中科院一区).
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L. Cheng, Y. Wang, Q. Liu, D. Epema, C. Liu, Y. Mao, J. Murphy. Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers. IEEE Transactions on Parallel and Distributed Systems, 2021 (CCF-A).
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M. Liu, L. Cheng (通讯), Y. Gu, Y. Wang, Q. Liu, N. O’Connor. MPC-CSAS: Multi-Party Computation for Real-time Privacy-preserving Speed Advisory Systems. IEEE Transactions on Intelligent Transportation Systems, 2021 (中科院一区).
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Q. Liu, L. Cheng (通讯), A. Jia, C. Liu. Deep Reinforcement Learning for Communication Flow Control in Wireless Mesh Networks. IEEE Network, 2021 (中科院一区, ESI高被引论文).
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C. Liu, Q. Zeng, L. Cheng (通讯), H. Duan, J. Cheng. Measuring Similarity for Data-aware Business Processes. IEEE Transactions on Automation Science and Engineering, 2020 (CCF-B).
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Q. Liu, L. Cheng, R. Alves, T. Ozcelebi, F. Kuipers, G. Xu, J. Lukkien, S. Chen. Cluster-based Flow Control in Hybrid Software-Defined Wireless Sensor Networks. Computer Networks, 2020 (CCF-B).
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J. Liu, H. Shen, H. Chi, H. Narman, Y. Yang, L. Cheng, W. Chung. A Low-cost Multi-failure Resilient Replication Scheme with Data Correlation for High Data Availability in Cloud Storage. IEEE/ACM Transactions on Networking, 29(4): 1436-1451, 2021 (CCF-A, ESI高被引论文).
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Y. Wang, Yc. Wang, C. Shi, L. Cheng, H. Li, X. Li. An Edge 3D CNN Accelerator for Low Power Activity Recognition. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020 (CCF-A).
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C. Liu, Q. Zeng, L. Cheng (通讯), H. Duan, M. Zhou, J. Cheng. Privacy-preserving Behavioral Correctness Verification of Cross-organizational Workflow with Task Synchronization Patterns. IEEE Transactions on Automation Science and Engineering, 2020 (CCF-B).
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L. Cheng, B. van Dongen, W. van der Aalst. Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment. IEEE Transactions on Services Computing, 2020. (CCF-A)
部分主持项目
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中车工业研究院项目:行车状态多参数自适应控制仿真测试与验证。2023,30万,项目负责人。
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国家电网科技项目:支撑分布式储能网络化运营关键技术研究。2021-2024,500万元,课题负责人。
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国家重点研发计划:保障冬奥赛事网络和系统不间断运行的XX关键技术研究与应用。2021-2022,1000万元,子课题负责人。
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欧盟H2020玛丽居里项目:大型分布式系统中网络感知的数据查询优化。2018-2019,20万欧元,项目负责人。
外校主要合作者
- Wil van der Aalst (欧洲科学院院士,洪堡教授,流程挖掘创始人)
- Schahram Dustdar (维也纳工业大学教授、欧洲科学院院士)
- Dick Epema (荷兰代尔夫特理工大学教授)
- Spyros Kotoulas (Facebook英国工程部经理)
- Markus Krötzsch (德国德累斯顿工业大学教授)
- Cong Liu (山东理工大学教授)
- Jinwei Liu (美国Florida A&M大学助理教授)
- Qingzhi Liu (荷兰Wageningen大学助理教授)
- Xiufeng Liu (丹麦科技大学副教授)
- Ying Mao (美国Fordham大学副教授)
- John Murphy (爱尔兰都柏林大学教授)
- Ilias Tachmazidis (英国Huddersfield大学高级讲师)
- Georgios Theodoropoulos (中国南方科技大学讲席教授)
- Tomas Ward (爱尔兰都柏林城市大学讲席教授)
- Ying Wang (中科院计算所研究员、国家优青)