基本信息
刘德彬，男，1997年生，2024年6月份于华中科技大学取得计算机系统结构专业工学博士学位，中共党员，副研究员，硕士生导师，CCF协同计算专业委员会委员，工业物联网技术与应用专委会委员。2024年8月入职郑州大学计算机与人工智能学院，主要研究方向有多模态学习、深度神经网络模型优化、3D点云生成、3D姿态迁移、神经网络模型压缩与加速、大模型高效推理等；在IEEE TPAMI、TIP、TPDS、TC、TIFS、TCAD、TITS、TII、ACM TOMM、IEEE Communications Surveys and Tutorials、ICME等期刊会议发表论文30余篇，获ICME（CCF B）最佳论文提名；担任国际顶级期刊/会议ACM MM，NeurlPS、AAAI、ICLR、CVPR、ICML、IEEE TIFS、TITS、TDSC、TMC、TNNLS、TII、TVT等审稿人。
学术论文
[1] Debin Liu, Xiang Bai, Ruonan Zhao, Xianjun Deng, and Laurence T. Yang. Dual-grained Lightweight Strategy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024, 46(12): 10228-10245 (IF: 18.6, 中科院一区Top, CCF A)
[2] Shijie Lv, Debin Liu (唯一通讯作者), Laurence T. Yang, Xiaosong Peng, Ruonan Zhao, Zecan Yang, and Jun Feng. Based on Tensor Core Sparse Kernels Accelerating Deep Neural Networks. IEEE Transactions on Parallel and Distributed Systems, 2025, doi: 10.1109/TPDS.2025.3637268 (IF: 6.0, 中科院二区, CCF A)
[3] Shijie Lv, Ruonan Zhao, Debin Liu (唯一通讯作者), Laurence T. Yang, and Jinhua Cui. QaQuant: Towards Efficient INT4 Quantization for High-Performance LLMs Services Deployment on Edge Devices. IEEE Transactions on Computers, 2025. (大修, IF: 3.8, 中科院二区, CCF A)
[4] Debin Liu, Laurence T. Yang, Ruonan Zhao, Jiawei Wang, and Xia Xie. Lightweight Tensor Deep Computation Model with Its Application in Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 2678-2687, 2022. (IF: 8.4, 中科院一区Top, CCF B)
[5] Debin Liu, Laurence T. Yang, Ruonan Zhao, Xianjun Deng, Chenlu Zhu, and Yiheng Ruan. Multi-tree Compact Hierarchical Tensor Recurrent Neural Networks for Intelligent Transportation Systems Edge Devices. IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 8, pp. 8719-8729, 2024. (IF:8.4, 中科院一区Top, CCF B)
[6] Jinglin Zhao, Debin Liu (唯一通信作者), Laurence T. Yang, Ruonan Zhao, Zheng Wang, and Zhe Li. TD3D: Tensor-based Discrete Diffusion Process for 3D Shape Generation. IEEE International Conference on Multimedia and Expo, 2024. (CCF B, 最佳论文提名)
[7] Ruonan Zhao, Laurence T. Yang, Debin Liu (唯一通信作者), and Wanli Lu. Tensor-empowered Communication-efficient and Trustworthy Federated Learning for Heterogeneous Intelligent Space-Air-Ground Integrated IoT. IEEE Internet of Things Journal, vol. 10, no. 23, pp. 20285-20296, 2023. (IF: 8.9, 中科院一区Top)
[8] Ruonan Zhao, Laurence T. Yang, Debin Liu (唯一通信作者), Xianjun Deng, Xueming Tang, and Sahil Garg. Tensor-based Secure Truthful Incentive Mechanism for Mobile Crowdsourcing in IoT-enabled Maritime Transportation Systems. IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 5, pp. 3341-3351, 2024. (IF: 8.4, 中科院一区Top, CCF B)
[9] Ruonan Zhao, Laurence T. Yang, Debin Liu (唯一通信作者), Wanli Lu, and Xiangli Yang. Lightweight Tensor-based GRU for Trustworthy and Communication Efficient Federated Learning in Industrial IoT. IEEE Transactions on Industrial Informatics, vol. 21, no. 3, pp. 2043-2052, 2025. (IF: 9.9, 中科院一区Top)
[10] Debin Liu, Laurence T. Yang, Puming Wang, Ruonan Zhao, and Qingchen Zhang. TT-TSVD: A Multi-modal Tensor Train Decomposition with Its Application in Convolutional Neural Networks for Smart Healthcare. ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 18, no. 41, pp. 1-17, 2022. (IF: 6.0, 中科院三区, CCF B)
[11] Debin Liu, Laurence T. Yang, Ruonan Zhao, Jinhua Cui, and Xiangli Yang. An Efficient Tensor-based Transformer for Industrial Internet of Things. IEEE Transactions on Network Science and Engineering, vol. 11, no. 3, pp. 2574-2585, 2024. (IF: 7.9, 中科院二区)
[12] Debin Liu, Laurence T. Yang, Ruonan Zhao, and Honglu Zhao. Tensor-empowered Hardware-friendly Lightweight Deep Neural Networks. IEEE Transactions on Consumer Electronics, vol. 71, no. 1, pp. 2175-2185, 2025. (IF: 10.9, 中科院二区)
[13] Haixv Lu, Debin Liu (唯一通信作者), Laurence T Yang, Ruonan Zhao, Shijie Lian, Songhe Yuan, and Junjie Su. A Zero-shot High-dimensional Feature Fusion with STF-GAN for Cross-domain Image Reconstruction. IEEE Journal of Selected Topics in Signal Processing, 2025, doi: 10.1109/JSTSP.2025.3600191. (IF: 13.7, 中科院二区)
[14] Haixv Lu, Debin Liu (唯一通信作者), Laurence T Yang, Ruonan Zhao, Shijie Lv, Jiawei Wang, and Xiaosong Peng. Share Token Tensorized Attention Fusion: Enhancing Audio-Visual Emotion Recognition for Consumer Electronics. IEEE Transactions on Consumer Electronics, 2025, doi: 10.1109/TCE.2025.3599517. (IF: 10.9, 中科院二区)
[15] Ruonan Zhao, Laurence T. Yang, Debin Liu (唯一通讯作者), Xiangli Yang, and Meiqi Wang. Tensor-empowered Lightweight Representations for Personalized Federated Learning in Heterogeneous 6G Networks. IEEE Network, vol. 39, no. 2, pp. 115-123, 2025. (IF:6.3, 中科院三区)
[16] Zecan Yang, Laurence T. Yang, Huaimin Wang, Honglu Zhao, and Debin Liu. Bayesian Nonnegative Tensor Completion with Automatic Rank Determination. IEEE Transactions on Image Processing, vol. 34, pp. 2036-2051, 2025. (IF: 13.7, 中科院一区Top, CCF A)
[17] Jun Feng, Xuchi Cheng, Hong Sun, Shunli Zhang, and Debin Liu. Panther: Pracical Secure 2-Party Neural Network Inference. IEEE Transactions on Information Forensics and Security, vol. 20, pp. 1149-1162. 2025. (IF: 8.0; 中科院一区Top；CCF A)
[18] Bocheng Ren, Yuanyuan Yi, Qingchen Zhang, and Debin Liu. Zero-Shot Image Recognition via Learning Dual Prototype Accordance Across Meta-Domains. IEEE Transactions on Image Processing, vol. 34, pp. 6361-6373, 2025. (IF: 13.7, 中科院一区Top, CCF A)
[19] Shuilong Wang, Laurence T Yang, Debin Liu, Ruonan Zhao, Xianjun Deng, Cannian Zou, and Xiaoxuan Fan. Improving Ethereum Mixing Address Linking with Tensor Computation, Neighbor Data Utilization and Asymmetric Information Modeling. IEEE Transactions on Information Forensics and Security, vol. 20, pp. 8658-8671. 2025. (IF: 8.0; 中科院一区Top；CCF A)
[20] Xiaosong Peng, Laurence T Yang, Xiaokang Wang, Debin Liu, and Jie Li. A High-Efficiency Parallel Mechanism for Canonical Polyadic Decomposition on Heterogeneous Computing Platform. IEEE Transactions on Computers, vol. 74, no. 10, pp. 3377-3389, 2025. (IF: 3.8, 中科院二区, CCF A)
[21] Kai Tang, Jinhua Cui, Changhao Wen, Shiqiang Nie, Debin Liu, Yaliang Zhao, and Laurence T Yang. WOM-FTL: An Efficient FTL for High-Density Flash Memory Through WOM-v Codes. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, doi: 10.1109/TCAD.2025.3571833. (IF: 2.9, 中科院三区, CCF A)
[22] Ruonan Zhao, Laurence T. Yang, Debin Liu, Xianjun Deng, and Yijun Mo. A Tensor-based Truthful Incentive Mechanism for Blockchain-enabled Space-Air-Ground Integrated Vehicular Crowdsensing. IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 2853-2862, 2022. (IF: 8.4, 中科院一区Top, CCF B)
[23] Ruonan Zhao, Laurence T. Yang, Debin Liu, Wanli Lu, Chenlu Zhu, and Yiheng Ruan. Tensor-empowered LSTM for Communication-efficient and Privacy-enhancd Cognitive Federated Learning in Intelligent Transportation Systems. ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 20, no. 33, pp. 1-21, 2023. (IF: 6.0, 中科院三区, CCF B)
[24] Ruonan Zhao, Laurence T. Yang, Debin Liu, Xiaokang Zhou, Xianjun Deng, and Xueming Tang. A Multi-modal Tensor Ring Decomposition for Communication-efficient and Trustworthy Federated Learning for Its Covid-19 Scenario. IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 5, pp. 3535-3547, 2024. (IF: 8.4; 中科院一区Top; CCF B)
[25] Laurence T. Yang, Ruonan Zhao, Debin Liu, Wanli Lu, and Xianjun Deng. Tensor Empowered Federated Learning for Cyber-Physical-Social Computing and Communication Systems. IEEE Communications Surveys and Tutorials, vol. 25, no. 3, pp. 1909-1940, 2023. (IF: 46.7; 中科院一区Top)
[26] Honglu Zhao, Laurence T. Yang, Zecan Yang, Debin Liu, Xin Nie, and Bocheng Ren. Sparse Bayesian Tensor Completion for Data Recovery in Intelligent IoT Systems. IEEE Internet of Things Journal, vol. 11, no. 15, pp. 25682-25693, 2024. (IF: 8.9, 中科院一区Top)
[27] Songhe Yuan, Laurence T Yang, Debin Liu, Xiaokang Wang, and Jieming Yang. THPFF: A tensor-based high-precision feature fusion model for multi-source data in smart healthcare systems. Information Fusion, vol. 124, pp.103324. 2025. (IF: 15.5, 中科院一区Top)
[28] Xueru Bai, Jieyuan Chen, Laurence T. Yang, Debin Liu, Cen Chen, Xiaokang Wang, and M. Jamal Deen. TT-RNNPool3D: A Tensor-based High-order RNNPool Model for Mobile Edge Consumer Applications. IEEE Transactions on Consumer Electronics, 2025, doi: 10.1109/TCE.2024.3435410. (IF: 10.9, 中科院二区)
科研项目经历
项目1: 国家自然科学基金青年基金项目-主持
项目2: 中国博士后科学基金面上项目-主持
项目3: 曙光信息产业（北京）有限公司开放课题项目-主持
项目4: 国家自然科学基金重点项目-安全关键汽车信息物理系统建模理论与系统设计(2020.01-2024.12)，课题骨干，参与
项目5: 华中科技大学人工智能与智能交通联合技术中心与湖北楚天智能交通有限公司合作项目-智慧交通运营监测指挥调度系统 (2021.04-2024.12)，项目骨干，参与
项目6: 科技创新2030“新一代人工智能（2030）”重大项目-人工智能基础模型关键技术研究 (2023.03-2024.03)，项目骨干，参与
项目7: 国家重点研发项目-基于时隙映射的细粒度三层软切片及基于New IP的确定性转发技术 (2020.11-2023.10)，课题骨干，参与
获奖情况
[1] 2025年 IEEE Cybermatics Congress (ICA3PP(CCF C类会议)/Blockchain/SmartData/CPSCom/iThings/GreenCom), 郑州, 河南, IEEE Excellent Organization Organization Award-Local Chiar
[2] 2024年 IEEE Technical Committee on Scalable Computing 杰出博士论文奖
[3] 2024年 IEEE AI+ Congress (TrustCom (CCF C类会议)/BigDataSE/CSE/EUC/iSCI), 三亚, 海南, IEEE Excellent Organization Award-Organizing Committee Chair
[4] 2024年 IEEE AI for Science Congress (ISPA (CCF C类会议)/BDCloud/SocialCom/SustainCom/SpaCCS), 开封, 河南, IEEE Outstanding Service Award-Organizing Committee Member
[5] 2023年 IEEE Cybermatics Congress(Blockchain/SmartData/CPSCom/IThings/CBD/ICPADS (CCF C类会议)), 海花岛, 海南, IEEE Distinguished Services Award-Local Chair
[6] 2023年 华中科技大学“达梦奖学金”
[7] 2022年 National CyberSecurity Center International Congress (IEEE TrustCom (CCF C类会议)/BigDataSE/CSE/EUC/iSCI), 武汉, 湖北, IEEE Outstanding Leadership Award-Publicity Chair
[8] 2021年 IEEE Hyper-Intelligence Congress (HPCC (CCF C类会议)/Smartcity/DSS/DependSys/GPC/DIKW), 海口, 海南, IEEE Outstanding Leadership Award-Publicity Chair
[9] 2018年 全国大学生电子设计竞赛全国二等奖
[10] 2017年 本科生“国家奖学金”
招生信息
欢迎对人工智能、计算机视觉、神经网络模型优化、多模态学习、大模型高效推理等方向感兴趣的同学加入，有意向的同学可以将本人简历发送至：debinliuhust@gmail.com，联系电话: 18569968326。
招生加分项：1）同学能够在短暂的学术研究里坚定自我选择、努力拔尖、坐的住冷板凳，方能出得了了不起的研究成果；2）具备较好的英语能力、数学基础和人工智能相关的基础；3）具备较好的行动力，能够及时行动，而不是一直处于想法阶段；4）具备较好的编程能力（如python等），熟悉深度学习框架（pytorch、tensorflow）；5）本科具有科研经历，竞赛经历。
后话：希望加入团队的学生，我们能够一起在科研中探索，彼此相互学习与成长，朝着自己原本的目的地逐步前进！
