姓名：罗辛
系别：计算机科学系
邮箱：[email protected] / [email protected]
【个人简介】
工学博士、博士后，西南大学二级教授、博士生导师，南宫娱乐
·软件南宫娱乐
院长，IEEE Fellow，国家高层次领军人才、中国科南宫娱乐
百人计划入选人。于2005年在电子科技大学计算机南宫娱乐
取得工学学士学位，2011年在北京航空航天大学计算机南宫娱乐
取得工学博士学位。研究聚焦数据科学领域，在IEEE T-PAMI、T-KDE、T-NNLS等国际期刊和WWW、ICDM等国际会议上发表学术论文350余篇（含中科院一区期刊论文120篇、IEEE Transactions/Journal论文151篇、ESI高引论文32篇），累计影响因子超过1000，Web of Science统计引用超过9000次，谷歌学术统计引用超过14,000次，H指数为74。先后主持国家级项目7项，省部级项目10余项，累积负责科研经费超过5000万元。获国家发明专利授权35项、实现27项授权专利的成果转化，累积产生经济效益超过2亿元。获重庆市自然科学一等奖（2019/第一完成人）、重庆市科技进步一等奖（2018/第二完成人）、中国人工智能学会吴文俊人工智能科技进步一等奖（2018/第三完成人）等科技奖励。现任神经网络领域国际著名期刊IEEE Transactions on Neural Networks and Learning Systems和中国科技期刊卓越行动计划重点类期刊IEEE/CAA Journal of Automatica Sinica的编委，获IEEE Transactions on Neural Networks and Learning Systems的2022-2024年度优秀编委奖、IEEE/CAA Journal of Automatica Sinica的2020年度优秀编委奖，自2022年起连续入选斯坦福与爱思唯尔全球前2%顶尖科学家“终身科学影响力”榜单和爱思唯尔“中国高被引学者”榜单。
【科研情况】
一、代表性项目
1．西南大学高层次人才支持项目，2023.03-2027.12，600万
2．西南大学青年科学家团队项目，2023.05-2026.05，160万
3．国家重点研发计划项目课题，贿赂犯罪社会关系网络的多粒度分析技术研究，2017/06-2021/06，724万
4．国家高层次人才特殊支持计划青年拔尖人才项目，2020/11-2023/11，160万
5．中国科南宫娱乐
百人计划青年俊才类择优支持项目，2018/12-2021/12，280万
6．国家自然科学基金面上项目，大规模属性异质图张量低秩学习方法，2023/01-2026/12，54万
7．国家自然科学基金面上项目，基于隐特征分析的信息推荐技术研究，2018/01-2021/12，66万
8．国家自然科学基金-英国皇家学会合作交流项目，基于大数据学习的云服务QoS分析与预测技术研究，2016/04-2018/03，20万
9．国家自然科学基金青年项目，增量协同过滤模型研究，2013/01-2015/12，25万
10．重庆市自然科学基金杰出青年项目，高维稀疏数据分析方法，2019/07-2022/06，50万
二、作为第一作者或通讯作者发表的IEEE TRANSACTIONS/JOURNAL论文
1. XinLuo（罗辛），Zhibin Li, Wenbin Yue*, and Shuai Li*. A Calibrator Fuzzy Ensemble forHighly-Accurate Robot Arm Calibration. IEEE Transactions on Neural Networksand Learning Systems, 10.1109/TNNLS.2024.3354080. IF=10.4，中科院一区，CCF-B类
2. YeYuan, Jinli Li, and Xin Luo*（罗辛）. A FuzzyPID-Incorporated Stochastic Gradient Descent Algorithm for Fast and AccurateLatent Factor Analysis. IEEE Transactions on Fuzzy Systems,10.1109/TFS.2024.3389733. IF=11.9，中科院一区，CCF-B类
3. JiufangChen#, Kechen Liu#, Xin Luo*（罗辛）, Ye Yuan, KhaledSedraoui, Yusuf Al-Turki, and MengChu Zhou. A State-migration Particle SwarmOptimizer for Adaptive Latent Factor Analysis of High-Dimensional andIncomplete Data. IEEE/CAA Journal of Automatica Sinica, 10.1109/JAS.2024.IF=11.8，中科院一区
4. WeiyiYang, Shuai Li, and Xin Luo*（罗辛）. Data DrivenVibration Control: A Review. IEEE/CAA Journal of Automatica Sinica,10.1109/JAS.2024.124431. IF=11.8，中科院一区
5. XinLiao, Khoi Hoang, and Xin Luo*（罗辛）. Local Search-basedAnytime Algorithms for Continuous Distributed Constraint OptimizationProblems. IEEE/CAA Journal of Automatica Sinica, 10.1109/JAS.2024.124413.IF=11.8，中科院一区
6. WenQin and Xin Luo*（罗辛）. AsynchronousParallel Fuzzy Stochastic Gradient Descent for High-Dimensional IncompleteData. IEEE Transactions on Fuzzy Systems, 2024, 32(2): 445-459. IF=11.9，中科院一区，CCF-B类
7. WenQin, Xin Luo*（罗辛）, and MengChu Zhou.Adaptively-accelerated Parallel Stochastic Gradient Descent forHigh-Dimensional and Incomplete Data Representation Learning, IEEE Transactionson Big Data, 2024, 10(1): 92-107. IF=7.2
8. TinghuiChen, Shuai Li, Yan Qiao, and Xin Luo*（罗辛）. A Robust and Efficient Ensemble of DiversifiedEvolutionary Computing Algorithms for Accurate Robot Calibration. IEEETransactions on Instrumentation and Measurement, 2024, 73:1-14. IF=5.6
9. NianyinZeng, Xinyu Li, Peishu Wu, Han Li, and Xin Luo*（罗辛）. A Novel Tensor Decomposition-based EfficientDetector for Low-altitude Aerial Objects with Knowledge Distillation Scheme.IEEE/CAA Journal of Automatica Sinica, 2024, 11(2): 487-501. IF=11.8，中科院一区
10. DiWu, Xin Luo*（罗辛）, Yi He and MengChuZhou. A Prediction-sampling-based Multilayer-structured Latent Factor Modelfor Accurate Representation to High-dimensional and Sparse Data. IEEETransactions on Neural Networks and Learning Systems, 2024, 35(3): 3845-3858.IF=10.4，中科院一区，CCF-B类
11. XinLuo（罗辛）, Yue Zhou, ZhigangLiu, and MengChu Zhou*. Fast and Accurate Non-negative Latent Factor Analysison High-dimensional and Sparse Matrices in Recommender Systems, IEEETransactions on Knowledge and Data Engineering, 2023, 35(4): 3897-3911.IF=8.9，CCF-A类，中科院一区
12. XinLuo*（罗辛）, Yurong Zhong, Zidong Wang, and Maozhen Li. AnAlternating-direction-method of Multipliers-Incorporated Approach toSymmetric Non-negative Latent Factor Analysis, IEEE Transactions on NeuralNetworks and Learning Systems, 2023, 34(8): 4826-4840. IF=10.4，中科院一区，CCF-B类
13. XinLuo（罗辛）, Liwei Wang, PengweiHu, and Lun Hu*. Predicting Protein-Protein Interactions Using Sequence andNetwork Information via Variational Graph Autoencoder. IEEE/ACM Transactionson Computational Biology and Bioinformatics, 2023, 20(5): 3182-3194. IF=4.5，CCF-B类
14. FanghuiBi, Xin Luo*（罗辛）, Bo Shen, HongliDong, and Zidong Wang. ProximalAlternating-Direction-Method-of-Multipliers-Incorporated Nonnegative LatentFactor Analysis. IEEE/CAA Journal of Automatica Sinica, 2023, 10(6):1388-1406. IF=11.8，中科院一区，谷歌学术引用10次
15. FanghuiBi, Tiantian He, Yuetong Xie, and Xin Luo*（罗辛）. Two-Stream Graph ConvolutionalNetwork-Incorporated Latent Feature Analysis, IEEE Transactions on ServicesComputing, 2023, 16(4): 3027-3042. IF=8.1，中科院一区，CCF-A类，谷歌学术引用13次
16. LunHu, Yue Yang, Zehai Tang, Yizhou He, and Xin Luo*（罗辛）. FCAN-MOPSO: An Improved Fuzzy-based GraphClustering Algorithm for Complex Networks with Multi-objective Particle SwarmOptimization. IEEE Transactions on Fuzzy Systems, vol. 31, no. 10, pp.3470-3484, Oct. 2023, 31(10): 3470-3484. IF=11.9，中科院一区，CCF-B类，谷歌学术引用33次
17. DiWu, Yi He, and Xin Luo*（罗辛）. A Graph-incorporatedLatent Factor Analysis Model for High-dimensional and Sparse Data. IEEETransactions on Emerging Topics in Computing, 2023, 11(4): 907-917. IF=5.9
18. WeiyiYang, Shuai Li, Zhibin Li, and Xin Luo*（罗辛）. Highly-Accurate Manipulator Calibration viaExtended Kalman Filter-Incorporated Residual Neural Network. IEEETransactions on Industrial Informatics, 2023, 19(11): 10831-10841. IF=12.3，中科院一区，谷歌学术引用15次
19. XinLuo（罗辛）, Hao Wu, and ZechaoLi*. NeuLFT: A Novel Approach to Nonlinear Canonical Polyadic Decompositionon High-Dimensional Incomplete Tensors, IEEE Transactions on Knowledge andData Engineering, 2023, 35(6): 6148-6166. IF=8.9，中科院一区，CCF-A类，谷歌学术引用104次
20. YeYuan, Xin Luo*（罗辛）, Mingsheng Shang, andZidong Wang. A Kalman-Filter-Incorporated Latent Factor Analysis Model forTemporally Dynamic Sparse Data. IEEE Transactions on Cybernetics, 2023,53(9): 5788-5801. IF=11.8，中科院一区，CCF-B类，谷歌学术引用35次
21. WeilingLi, Xin Luo*（罗辛）, Huaqiang Yuan, andMengChu Zhou. A Momentum-accelerated Hessian-vector-based Latent FactorAnalysis Model, IEEE Transactions on Services Computing, 2023, 16(2):830-844. IF=8.1，中科院一区，CCF-A类，谷歌学术引用22次
22. DiWu, Peng Zhang, Yi He, and Xin Luo*（罗辛）.A Double-Space and Double-Norm Ensembled Latent Factor Model for HighlyAccurate Web Service QoS Prediction, IEEE Transactions on Services Computing,2023, 16(2): 802-814. IF=8.1，中科院一区，CCF-A类，谷歌学术引用59次
23. ZhibinLi, Shuai Li, Omaimah Bamasag, Areej Alhothali, and Xin Luo*（罗辛）. Diversified Regularization Enhanced Training forEffective Manipulator Calibration. IEEE Transactions on Neural Networks andLearning Systems, 2023, 34(11): 8778-8790. IF=10.4，中科院一区，CCF-B类，谷歌学术引用59次
24. LinChen, and Xin Luo*（罗辛）. Tensor DistributionRegression based on the 3D Conventional Neural Networks. IEEE/CAA Journal ofAutomatica Sinica, 2023, 10(7): 1628-1630. IF=11.8，中科院一区，
25. ZhigangLiu, Yugen Yi, and Xin Luo*（罗辛）. A High-OrderProximity-Incorporated Nonnegative Matrix Factorization-based CommunityDetector. IEEE Transactions on Emerging Topics in Computational Intelligence,2023, 7(3): 700-714. IF=5.3
26. ZhengtaiXie, Long Jin*, and Xin Luo*（罗辛）. Kinematics-BasedMotion-Force Control for Redundant Manipulators with Quaternion Control. IEEETransactions on Automation Science and Engineering, 2023, 20(3): 1815-1828.IF=5.6，中科院一区，CCF-B类
27. MinzhiChen, Chunlin He*, and Xin Luo*（罗辛）.MNL: A Highly-Efficient model for Large-scale Dynamic Weighted DirectedNetwork Representation, IEEE Transactions on Big Data, 2023, 9(3): 889-903.IF=7.2，谷歌学术引用13次
28. WeilingLi#, Renfang Wang#, Xin Luo*（罗辛）, and MengChu Zhou*. ASecond-order Symmetric Non-negative Latent Factor Model for UndirectedWeighted Network Representation, IEEE Transactions on Network Science andEngineering, 2023, 10(2): 606-618. IF=6.6，谷歌学术引用11次
29. YueZhou, Xin Luo*（罗辛）, and MengChu Zhou*.Cryptocurrency Transaction Network Embedding from Static and DynamicPerspectives: An Overview. IEEE/CAA Journal of Automatica Sinica, 2023,10(5): 1105-1121. IF=11.8，中科院一区，谷歌学术引用10次
30. ZhibinLi, Xin Luo*（罗辛）, and Shuai Li*.Efficient Industrial Robot Calibration via a Novel Unscented Kalman Filter-IncorporatedVariable Step-Size Levenberg-Marquardt Algorithm. IEEE Transactions onInstrumentation and Measurement, 2023, 72: 1-12. IF=5.6
31. XiuqinXu, Mingwei Lin*, Xin Luo*（罗辛）, and Zeshui Xu.HRST-LR: A Hessian Regularization Spatio-Temporal Low Rank Algorithm forTraffic Data Imputation. IEEE Transactions on Intelligent TransportationSystems, 2023, 24(10): 11001-11017. IF=8.5，中科院一区，谷歌学术引用17次
32. XinLuo*（罗辛）, Jiufang Chen, Ye Yuan, and Zidong Wang. PseudoGradient-Adjusted Particle Swarm Optimization for Accurate Adaptive LatentFactor Analysis. IEEE Transactions on Systems Man Cybernetics: Systems,10.1109/TSMC.2023.3340919. IF=8.7，中科院一区，CCF-B类
33. WenQin, Xin Luo*（罗辛）, Shuai Li, andMengChu Zhou*. Parallel Adaptive Stochastic Gradient Descent Algorithms forLatent Factor Analysis of High-Dimensional and Incomplete Industrial Data.IEEE Transactions on Automation Science and Engineering,10.1109/TASE.2023.3267609. IF=5.6，中科院一区，CCF-B类
34. DiWu, Zechao Li, Zhikai Yu, Yi He, and Xin Luo*（罗辛）. Robust Low-rank Latent Feature Analysis forSpatio-Temporal Signal Recovery. IEEE Transactions on Neural Networks andLearning Systems, 10.1109/TNNLS.2023.3339786. IF=10.4，中科院一区，CCF-B类
35. FanghuiBi, Tiantian He, and Xin Luo*（罗辛）. A Fast NonnegativeAutoencoder-based Approach to Latent Feature Analysis on High-Dimensional andIncomplete Data, IEEE Transactions on Services Computing,10.1109/TSC.2023.3319713. IF=8.1，中科院一区，CCF-A类
36. DiWu, Peng Zhang, Yi He, and Xin Luo*（罗辛）.MMLF: Multi-Metric Latent Feature Analysis for High-Dimensional andIncomplete Data, IEEE Transactions on Services Computing,10.1109/TSC.2023.3331570. IF=8.1，中科院一区，CCF-A类
37. YeYuan, Xin Luo*（罗辛）, and MengChu Zhou.Adaptive Divergence-based Non-negative Latent Factor Analysis ofHigh-Dimensional and Incomplete Matrices from Industrial Applications. IEEETransactions on Emerging Topics in Computational Intelligence, 10.1109/TETCI.2023.3332550.IF=5.3
38. LongJin, Siqi Liang, Xin Luo*（罗辛）, and Mengchu Zhou.Distributed and Time-Delayed k-Winner-Take-All Network for CompetitiveCoordination of Multiple Robots. IEEE Transactions on Cybernetics, 2023,53(1): 641-652. IF=11.8，中科院一区，CCF-B类，谷歌学术引用26次
39. WeilingLi, Renfang Wang, and Xin Luo*（罗辛）. A GeneralizedNesterov-Accelerated Second-Order Latent Factor Model for High-Dimensionaland Incomplete Data. IEEE Transactions on Neural Networks and LearningSystems, 10.1109/TNNLS.2023.3321915. IF=10.4，中科院一区，CCF-B类
40. ZhibinLi#, Shuai Li#, and Xin Luo*（罗辛）. A Novel MachineLearning System for Industrial Robot Arm Calibration. IEEE Transactions onCircuits and Systems II: Express Briefs, 10.1109/TCSII.2023.3332825. IF=4.4
41. FanZhang, Long Jin* and Xin Luo*（罗辛）. Error-SummationEnhanced Newton Algorithm for Model Predictive Control of RedundantManipulators. IEEE Transactions on Industrial Electronics, 2023, 70(3):2800-2811. IF=7.7，中科院一区，谷歌学术引用15次
42. LongJin*, Yutong Li, Xiaoyan Zhang, and Xin Luo*（罗辛）. Fuzzy k-Winner-Take-All Network for CompetitiveCoordination in Multi-robot Systems. IEEE Transactions on Fuzzy Systems,10.1109/TFS.2023.3339654. IF=11.9，中科院一区，CCF-B类
43. ZhengtaiXie, Long Jin*, Xin Luo*（罗辛）, MengChu Zhou, and YuZheng. A Biobjective Scheme for Kinematic Control of Mobile Robotic Arms withManipulability Optimization. IEEE/ASME Transactions on Mechatronics,10.1109/TMECH.2023.3313516. IF=6.4，中科院一区
44. ZhigangLiu, Xin Luo*（罗辛）, and MengChu Zhou.Symmetry and Graph Bi-regularized Non-Negative Matrix Factorization forPrecise Community Detection. IEEE Transactions on Automation Science andEngineering, 10.1109/TASE.2023.3240335. IF=5.6，中科院一区，CCF-B类，谷歌学术引用18次
45. JinliLi, Xin Luo*（罗辛）, Ye Yuan, and ShaoceGao. A Nonlinear PID-Incorporated Adaptive Stochastic Gradient DescentAlgorithm for Latent Factor Analysis. IEEE Transactions on Automation Scienceand Engineering, 10.1109/TASE.2023.3284819. IF=5.6，中科院一区，CCF-B类
46. MinzhiChen, Yan Qiao, Renfang Wang*, and Xin Luo*（罗辛）. A Generalized Nesterov’sAccelerated Gradient-Incorporated Non-negativeLatent-factorization-of-tensors Model for Efficient Representation to DynamicQoS Data. IEEE Transactions on Emerging Topics in Computational Intelligence,10.1109/TETCI.2024.3360338. IF=5.3
47. XinLuo（罗辛）, Hao Wu, Zhi Wang,Jianjun Wang, and Deyu Meng*. A Novel Approach to Large-Scale DynamicallyWeighted Directed Network Representation, IEEE Transactions on PatternAnalysis and Machine Intelligence, 2022, 44(12): 9756-9773. IF=23.6，中科院一区，CCF-A类，谷歌学术引用143次
48. XinLuo（罗辛）, Ye Yuan, Sili Chen,Nianyin Zeng, and Zidong Wang. Position-Transitional Particle SwarmOptimization-Incorporated Latent Factor Analysis, IEEE Transactions onKnowledge and Data Engineering, 2022, 34(8): 3958-3970. IF=8.9，中科院一区，CCF-A类，谷歌学术引用218次
49. XinLuo（罗辛）, Yue Zhou, ZhigangLiu, Lun Hu*, and MengChu Zhou*. Generalized Nesterov’sAcceleration-incorporated, Non-negative and Adaptive Latent Factor Analysis,IEEE Transactions on Services Computing, 2022, 15(5): 2809-2823. IF=8.1，中科院一区，CCF-A类，谷歌学术引用73次
50. XinLuo（罗辛）, Minzhi Chen, Hao Wu,Zhigang Liu, Huaqiang Yuan*, and MengChu Zhou*. Adjusting Learning Depth inNon-negative Latent Factorization of Tensors for Accurately Modeling TemporalPatterns in Dynamic QoS Data, IEEE Transactions on Automation Science andEngineering, 2022, 18(4): 2142-2155. IF=5.6，中科院一区，CCF-B类，谷歌学术引用53次
51. XinLuo（罗辛）, Zhigang Liu, LongJin*, Yue Zhou, and MengChu Zhou*. Symmetric Non-negative MatrixFactorization-based Community Detection Models and Their ConvergenceAnalysis. IEEE Transactions on Neural Networks and Learning Systems, 2022,33(3): 1203-1215. IF=10.4，中科院一区，CCF-B类，，谷歌学术引用116次
52. DiWu#, Xin Luo#,*（罗辛）, Mingsheng Shang, YiHe, Guoyin Wang, and Xindong Wu. A Data-Characteristic-Aware Latent FactorModel for Web Services QoS Prediction, IEEE Transactions on Knowledge andData Engineering, 2022, 34(6): 2525-2538. IF=8.9，中科院一区，CCF-A类，谷歌学术引用183次，ESI高引
53. LunHu#, Sicheng Yan#, Xin Luo*（罗辛）, and MengChu Zhou. AnAlgorithm of Inductively Identifying Clusters from Attributed Graphs, IEEETransactions on Big Data, 2022, 8(2): 523-534. IF=7.2，谷歌学术引用57次，ESI高引
54. XiaoyuShi#, Qiang He#, Xin Luo*（罗辛）, Yanan Bai, andMingsheng Shang#. Large-scale and Scalable Latent Factor Analysis viaDistributed Alternative Stochastic Gradient Descent for Recommender Systems,IEEE Transactions on Big Data, 2022, 8(2):420-431. IF=7.2，谷歌学术引用103次，ESI高引
55. HaoWu#, Xin Luo*（罗辛）, and MengChu Zhou#.Advancing Non-negative Latent Factorization of Tensors with DiversifiedRegularizations, IEEE Transactions on Services Computing, 2022, 15(3):1334-1344. IF=8.1，中科院一区，谷歌学术引用123次，CCF-A类，ESI高引
56. YurongZhong, Long Jin, Mingsheng Shang, and Xin Luo*（罗辛）. Momentum-incorporated Symmetric Non-negativeLatent Factor Models, IEEE Transactions on Big Data, 2022, 8(4): 1096-1106.IF=7.2，谷歌学术引用11次
57. YeYuan#, Qiang He#, Xin Luo#,*（罗辛）, and MingshengShang*. A Multilayered-and-Randomized Latent Factor Model forHigh-Dimensional and Sparse Matrices, IEEE Transactions on Big Data, 2022,8(3): 784-794. IF=7.2，谷歌学术引用70次
58. MingshengShang, Ye Yuan, Xin Luo*（罗辛）, and Mengchu Zhou. Anα-β-divergence-generalizedRecommender for Highly-accurate Predictions of Missing User Preferences, IEEETransactions on Cybernetics, 2022, 52(8): 8006-8018. IF=11.8，中科院一区，CCF-B类，谷歌学术引用75次
59. DiWu#, Qiang He, Xin Luo*（罗辛）, Mingsheng Shang#, YiHe, and Guoyin Wang. A Posterior-neighborhood-regularized Latent Factor Modelfor Highly Accurate Web Service QoS Prediction, IEEE Transactions on ServicesComputing, 2022, 15(2): 793-805. IF=8.1，中科院一区，CCF-A类，谷歌学术引用120次，ESI高引
60. DongdongCheng, Jinlong Huang*, Sulan Zhang, Xiaohua Zhang, and Xin Luo*（罗辛）. A Novel Approximate Spectral Clustering Algorithmwith Dense Cores and Density Peaks. IEEE Transactions on Systems ManCybernetics: Systems, 2022, 52(4): 2348-2360. IF=8.7，中科院一区，CCF-B类，谷歌学术引用32次
61. DiWu, Yi He, Xin Luo*（罗辛）, and MengChu Zhou. ALatent Factor Analysis-based Approach to Online Sparse Streaming FeatureSelection. IEEE Transactions on Systems Man Cybernetics: Systems, 2022,52(11): 6744-6758. IF=8.7，中科院一区，CCF-B类，谷歌学术引用136次
62. LunHu, Xiangyu Pan, Zehai Tang, and Xin Luo*（罗辛）. A Fast Fuzzy Clustering Algorithm for ComplexNetworks via a Generalized Momentum Method. IEEE Transactions on FuzzySystems, 2022, 30(9): 3473-348. IF=11.9，中科院一区，CCF-B类，谷歌学术引用71次，ESI高引
63. DiWu#, Mingsheng Shang, Xin Luo#,*（罗辛）,and Zidong Wang. An L1-and-L2-norm-oriented Latent Factor Model forRecommender Systems, IEEE Transactions on Neural Networks and LearningSystems, 2022, 33(10): 5775-5788. IF=10.4，中科院一区，CCF-B类，谷歌学术引用134次
64. JiaChen, Xin Luo*（罗辛）, and MengChu Zhou.Hierarchical Particle Swarm Optimization-incorporated Latent Factor Analysisfor Large-Scale Incomplete Matrices, IEEE Transactions on Big Data, 2022,8(6): 1524-1536. IF=7.2，谷歌学术引用65次
65. YanSong, Zhengyu Zhu, Ming Li, Guisong Yang, and Xin Luo*（罗辛）. Non-negative Latent Factor Analysis-Incorporatedand Feature-Weighted Fuzzy Double c-Means Clustering for Incomplete Data.IEEE Transactions on Fuzzy Systems, 2022, 30(10): 4165-4176. IF=11.9，中科院一区，CCF-B类，谷歌学术引用22次
66. QingxianWang, Xinyu Liu, Tianqi Shang, Zhigang Liu, Han Yang, and Xin Luo*（罗辛）. Multi-Constrained Embedding for Accurate CommunityDetection on Undirected Networks, IEEE Transactions on Network Science andEngineering, 2022, 9(5): 3675-3690. IF=6.6
67. LongJin, Xin Zheng, and Xin Luo*（罗辛）. Neural Dynamics forDistributed Collaborative Control of Manipulators with Time Delays. IEEE/CAAJournal of Automatica Sinica, 2022, 9(5): 854-863. IF=11.8，中科院一区，谷歌学术引用41次
68. ZhigangLiu, Guanxiao Yuan, and Xin Luo*（罗辛）.Symmetry and Nonnegativity-Constrained Matrix Factorization for CommunityDetection. IEEE/CAA Journal of Automatica Sinica, 2022, 9(9) 1691-1693.IF=11.8，中科院一区，谷歌学术引用22次
69. YimengQi#, Long Jin#,*, Xin Luo*（罗辛）, Yang Shi, and MeiLiu. Robust k-WTA Network Generation, Analysis, and Applications toMulti-Agent Coordination. IEEE Transactions on Cybernetics, 2022, 52(8):8515-8527. IF=11.8，中科院一区，CCF-B类，谷歌学术引用34次
70. LunHu, Sicheng Yang, Xin Luo*（罗辛）, Huaqiang Yuan*, andMengChu Zhou. A Distributed Framework for Large-scale Protein-proteinInteraction Data Analysis and Prediction Using MapReduce. IEEE/CAA Journal ofAutomatica Sinica, 2022, 9(1): 160-172. IF=11.8，中科院一区，谷歌学术引用66次
71. HaoWu, Xin Luo*（罗辛）, MengChu Zhou*,Muhyaddin J. Rawa, Khaled Sedraoui, and Aiiad Albeshri. A PID-incorporatedLatent Factorization of Tensors Approach to Dynamically Weighted DirectedNetwork Analysis. IEEE/CAA Journal of Automatica Sinica, 2022, 9(3): 533-546.IF=11.8，中科院一区，谷歌学术引用54次
72. LongJin, Yimeng Qi, Xin Luo*（罗辛）, Shuai Li*, andMingsheng Shang. Distributed Competition of Multi-Robot Coordination underVariable and Switching Topologies. IEEE Tran sactions on Automation Scienceand Engineering, 2022, 19(4): 3575-3586. IF=5.6，中科院一区，CCF-B类，谷歌学术引用22次
73. LinWei, Long Jin*, and Xin Luo*（罗辛）. Noise-SuppressingNeural Dynamics for Time-Dependent Constrained Nonlinear Optimization WithApplications. IEEE Transactions on Systems Man Cybernetics: Systems, 2022,52(10): 6139-6150. IF=8.7，中科院一区，CCF-B类，谷歌学术引用27次
74. ZhibinLi, Shuai Li*, and Xin Luo*（罗辛）. Using QuadraticInterpolated Beetle Antennae Search to Enhance Robot Arm CalibrationAccuracy. IEEE Robotics and Automation Letters, 2022, 7(4): 12046-12053.IF=5.2，谷歌学术引用16次
75. ZhibinLi, Shuai Li*, and Xin Luo*（罗辛）. A Novel CalibrationSystem for Robot Arm via An Open Dataset and A Learning Perspective. IEEETransactions on Circuits and Systems II: Express Briefs, 2022, 69(12):5169-5173. IF=4.4，谷歌学术引用15次
76. YimengQi#, Long Jin#,*, Xin Luo*（罗辛）, and MengChu Zhou.Recurrent Neural Dynamics Models for Perturbed Nonstationary QuadraticPrograms: A Control-theoretical Perspective. IEEE Transactions on NeuralNetworks and Learning Systems, 2022, 33(3): 1216-1227. IF=10.4，中科院一区，CCF-B类，谷歌学术引用28次
77. ZhengtaiXie#, Long Jin#,*, Xin Luo*（罗辛）, Zhongbo Sun, and MeiLiu. RNN for Repetitive Motion Generation of Redundant Robot Manipulators: AnOrthogonal Projection Based Scheme. IEEE Transactions on Neural Networks andLearning Systems, 2022, 33(2): 615-628. IF=10.4，中科院一区，CCF-B类，谷歌学术引用80次，ESI高引
78. XinLuo#（罗辛）, Dexian Wang#, MengChu Zhou*, and Huanqiang Yuan*.Latent Factor-based Recommenders Relying on Extended Stochastic GradientDescent Algorithms. IEEE Transactions on Systems Man Cybernetics: Systems,2021, 51(2): 916-926. IF=8.7，中科院一区，CCF-B类，谷歌学术引用143次，ESI高引
79. XinLuo#,*（罗辛）, Zhigang Liu#, Shuai Li, Mingsheng Shang, andZidong Wang, A Fast Non-negative Latent Factor Model based on GeneralizedMomentum Method. IEEE Transactions on Systems Man Cybernetics: Systems, 2021,51(1): 610-620. IF=8.7，中科院一区，CCF-B类，谷歌学术引用179次，ESI高引
80. WeilingLi#, Qiang He#, Xin Luo*（罗辛）, and Zidong Wang.Assimilating Second-Order Information for Building Non-Negative Latent FactorAnalysis-Based Recommenders. IEEE Transactions on Systems Man Cybernetics:Systems, 2021, 52(1): 485-497. IF=8.7，中科院一区，CCF-B类，谷歌学术引用25次
81. XinLuo（罗辛）, Zidong Wang*, andMingsheng Shang*. An Instance-frequency-weighted Regularization Scheme forNon-negative Latent Factor Analysis on High Dimensional and Sparse Data. IEEETransactions on Systems Man Cybernetics: Systems, 2021, 51(6): 3522-3532.IF=8.7，中科院一区，CCF-B类，谷歌学术引用118次
82. XinLuo#（罗辛）, Ye Yuan#, MengChu Zhou*, Zhigang Liu, andMingsheng Shang*. Non-negative Latent Factor Model based on β-divergencefor Recommender Systems. IEEE Transactions on Systems Man Cybernetics:Systems, 2021, 51(8): 4612-4623. IF=8.7，中科院一区，CCF-B类，谷歌学术引用96次
83. XinLuo*（罗辛）, MengChu Zhou, Shuai Li, and Mingsheng Shang*.Algorithms of Unconstrained Non-negative Latent Factor Analysis forRecommender Systems, IEEE Transactions on Big Data, 2021, 7(1): 227-240.IF=7.2，谷歌学术引用146次，ESI高引
84. XinLuo#（罗辛）, Wen Qin#, Ani Dong, Khaled Sedraoui, and MengChuZhou*, Efficient and High-quality Recommendations via Momentum-incorporatedParallel Stochastic Gradient Descent-based Learning, IEEE/CAA Journal ofAutomatica Sinica, 2021, 8(2): 402-411. IF=11.8，中科院一区，谷歌学术引用143次
85. XinLuo（罗辛）, Zhigang Liu,Mingsheng Shang, Jungang Lou*, and MengChu Zhou*. Highly-Accurate CommunityDetection via Pointwise Mutual Information-Incorporated SymmetricNon-negative Matrix Factorization, IEEE Transactions on Network Science andEngineering, 2021, 8(1): 463-476. IF=6.6，谷歌学术引用99次
86. DiWu#, Xin Luo*（罗辛）, Mingsheng Shang#, YiHe, Guoyin Wang, and Mengchu Zhou. A Deep Latent Factor Model forHigh-Dimensional and Sparse Matrices in Recommender Systems. IEEETransactions on Systems Man Cybernetics: Systems, 2021, 51(7): 4285-4296.IF=8.7，中科院一区，CCF-B类，谷歌学术引用183次，ESI高引
87. LunHu, Jun Zhang, Xiangyu Pan, Xin Luo（罗辛）*,and Huaqiang Yuan*. An Effective Link-based Clustering Algorithm forDetecting Overlapping Protein Complexes in Protein-protein InteractionNetworks, IEEE Transactions on Network Science and Engineering, 2021, 8(4):3275-3289. IF=6.6，谷歌学术引用41次
88. ZhigangLiu, Xin Luo*（罗辛）, and Zidong Wang.Convergence Analysis of Single Latent Factor-dependent, Non-negative andMultiplicative Update-based Non-negative Latent Factor Models. IEEETransactions on Neural Networks and Learning Systems, 2021, 32(4): 1737-1749.IF=10.4，中科院一区，CCF-B类，谷歌学术引用85次
89. DiWu, and Xin Luo*（罗辛）, Robust Latent FactorAnalysis for Precise Representation of High-dimensional and Sparse Data,IEEE/CAA Journal of Automatica Sinica, 2021, 8(4): 796-805. IF=11.8，中科院一区，谷歌学术引用102次
90. ZhibinLi, Shuai Li, and Xin Luo*（罗辛）, An Overview ofCalibration Technology of Industrial Robots, IEEE/CAA Journal of AutomaticaSinica, 2021, 8(1): 23-36. IF=11.8，中科院一区，谷歌学术引用188次
91. LongJin*,#, Jiazheng Zhang#, Xin Luo*（罗辛）,Mei Liu#, Shuai Li#, Lin Xiao, and Zihao Yang. Perturbed Manipulability Optimizationin A Distributed Network of Redundant Robots. IEEE Transactions on IndustrialElectronics, 2021, 68(8): 7209-7220. IF=7.7，中科院一区，谷歌学术引用42次
92. QinglanPeng, Yunni Xia*, MengChu Zhou, Xin Luo*（罗辛）, Shu Wang, Yuandou Wang, Chunrong Wu, ShanchenPang, and Mingwei Lin. Reliability-Aware and Deadline-Constrained MobileService Composition Over Opportunistic Networks. IEEE Transactions onAutomation Science and Engineering, 2021, 18(3): 1012-1025. IF=5.6，中科院一区，CCF-B类，谷歌学术引用18次
93. XinLuo（罗辛）, Hao Wu, MengChu Zhou*and Huaqiang Yuan*. Temporal Pattern-aware QoS Prediction via BiasedNon-negative Latent Factorization of Tensors. IEEE Transactions onCybernetics, 2020, 50(5): 1798-1809. IF=11.8，中科院一区，CCF-B类，谷歌学术引用255次，ESI高引
94. XinLuo#,*（罗辛）, MengChu Zhou*, Shuai Li, Lun Hu#, and MingshengShang, Non-negativity Constrained Missing Data Estimation forHigh-dimensional and Sparse Matrices from Industrial Applications. IEEETransactions on Cybernetics, 2020, 50(5): 1844-1855. IF=11.8，中科院一区，CCF-B类，谷歌学术引用116次
95. YanSong, Ming Li, Xin Luo*（罗辛）, Guisong Yang andChongjing Wang. Improved Symmetric and Nonnegative Matrix FactorizationModels for Undirected, Sparse and Large-Scaled Networks: A TripleFactorization-Based Approach. IEEE Transactions on Industrial Informatics,2020, 16(5): 3006-3017. IF=12.3，中科院一区，谷歌学术引用113次
96. LunHu, Pengwei Hu, Xiaohui Yuan, Xin Luo*（罗辛）, and Zhuhong You. Incorporating the CoevolvingInformation of Substrates in Predicting HIV-1 Protease Cleavage Sites.IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020,17(6): 2017-2028. IF=4.5，CCF-B类，谷歌学术引用41次
97. AmeerHamza Khan, Shuai Li*, and Xin Luo*（罗辛）.Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: AnRNN based Metaheuristic Approach. IEEE Transactions on Industrial Informatics,2020, 16(7): 4670-4680. IF=12.3，中科院一区，谷歌学术引用211次，ESI高引
98. DechaoChen#, Shuai Li, Qing Wu, and Xin Luo#（罗辛）. New Disturbance Rejection Constraint for RedundantRobot Manipulators: An Optimization Perspective. IEEE Transactions onIndustrial Informatics, 2020, 16(4): 2221-2232. IF=12.3，中科院一区，谷歌学术引用88次，ESI高引
99. XinLuo*（罗辛）, MengChu Zhou, Zidong Wang, Yunni Xia, andQingsheng Zhu. An Effective Scheme for QoS Estimation via AlternatingDirection Method-Based Matrix Factorization, IEEE Transactions on ServicesComputing, 2019, 12(4): 503-518. IF=8.1，中科院一区，CCF-A类，谷歌学术引用140次，ESI高引
100. XinLuo（罗辛） and MengChu Zhou*.Effects of Extended Stochastic Gradient Descent Algorithms on ImprovingLatent Factor-based Recommender Systems. IEEE Robotics and AutomationLetters, 2019, 4(2): 618-624. IF=5.2，谷歌学术引用16次
101. LunHu, Xiaohui Yuan, Xing Liu, Shengwu Xiong*, and Xin Luo*（罗辛）. Efficiently Detecting Protein Complexes fromProtein Interaction Networks via Alternating Direction Method of Multipliers.IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019,16(6): 1922-1935. IF=4.5，CCF-B类，谷歌学术引用88次
102. MingshengShang#, Xin Luo#,*（罗辛）, Zhigang Liu, JiaChen, Ye Yuan, and MengChu Zhou*, Randomized Latent Factor Model forHigh-dimensional and Sparse Matrices from Industrial Applications, IEEE/CAAJournal of Automatica Sinica, 2019, 6(1): 131-141. IF=11.8，中科院一区，谷歌学术引用122次
103. XinLuo*（罗辛）, MengChu Zhou, Shuai Li, Yunni Xia, Zhuhong You,Qingsheng Zhu, and Hareton Leung. Incorporation of Efficient Second-orderSolvers into Latent Factor Models for Accurate Prediction of Missing QoSData. IEEE Transactions on Cybernetics, 2018, 48(4): 1216-1228. IF=11.8，中科院一区，CCF-B类，谷歌学术引用243次，ESI高引
104. XinLuo*（罗辛）, MengChu Zhou, Shuai Li, and Mingsheng Shang. AnInherently Non-negative Latent Factor Model for High-dimensional and SparseMatrices from Industrial Applications. IEEE Transactions on IndustrialInformatics, 2018, 14 (5): 2011-2022. IF=12.3，中科院一区，谷歌学术引用193次，ESI高引
105. ShuaiLi#, MengChu Zhou*, and Xin Luo*,#（罗辛）.Modified Primal-Dual Neural Networks for Motion Control of RedundantManipulators With Dynamic Rejection of Harmonic Noises. IEEE Transactions onNeural Networks and Learning Systems, 2018, 29(10): 4791-4801. IF=10.4，中科院一区，CCF-B类，谷歌学术引用148次
106. XinLuo*（罗辛）, Jianpei Sun, Zidong Wang, Shuai Li, and MingshengShang. Symmetric and Non-negative Latent Factor Models for Undirected, HighDimensional and Sparse Networks in Industrial Applications. IEEE Transactionson Industrial Informatics, 2017, 13(6): 3098-3107. IF=12.3，中科院一区，谷歌学术引用145次
107. LongJin, Shuai Li*, Hung Manh La, and Xin Luo*,#（罗辛）. Manipulability Optimization of RedundantManipulators Using Dynamic Neural Networks. IEEE Transactions on IndustrialElectronics, 2017, 64(6): 4710-4720. IF=7.7，中科院一区，谷歌学术引用335次，ESI高引
108. XinLuo*（罗辛）, MengChu Zhou, Shuai Li, Zhuhong You, Yunni Xia,and Qingsheng Zhu. A Nonnegative Latent Factor Model for Large-Scale SparseMatrices in Recommender Systems via Alternating Direction Method. IEEETransactions on Neural Networks and Learning Systems, 2016, 27(3):524-537.IF=10.4，中科院一区，CCF-B类，谷歌学术引用315次，ESI高引
109. XinLuo*（罗辛）, MengChu Zhou, Yunni Xia, Qingsheng Zhu, AhmedChiheb Ammari, and Ahmed Alabdulwahab. Generating Highly Accurate Predictionsfor Missing QoS-data via Aggregating Non-negative Latent Factor Models. IEEETransactions on Neural Networks and Learning Systems, 2016, 27(3): 579-592.IF=10.4，中科院一区，CCF-B类，谷歌学术引用256次，ESI高引
110. XinLuo*（罗辛）,MengChu Zhou, Yunni Xia, and Qingsheng Zhu. AnIncremental-and-Static-Combined Scheme for Matrix-Factorization-BasedCollaborative Filtering. IEEE Transactions on Automation Science andEngineering, 2016, 13(1): 333-343. IF=5.6，中科院一区，CCF-B类，谷歌学术引用130次
111. XinLuo*（罗辛）, MengChu Zhou, Shuai Li, Zhuhong You, Yunni Xia,Qingsheng Zhu, and Hareton Leung. An Efficient Second-order Approach toFactorizing Sparse Matrices in Recommender Systems. IEEE Transactions on IndustrialInformatics. 2015, 11(4): 946-956. IF=12.3，中科院一区，谷歌学术引用113次
112. XinLuo*（罗辛）, MengChu Zhou, Yunni Xia, and Qingsheng Zhu. AnEfficient Non-negative Matrix-factorization-based Approach toCollaborative-filtering for Recommender Systems. IEEE Transactions onIndustrial Informatics, 2014, 10(2): 1273-1284. IF=12.3，中科院一区，谷歌学术引用693次，ESI高引
【获奖情况】
1. 2024年，IEEE Fellow（国际电气与电子工程师协会会士）
2. 2024年，国家高层次人才特殊支持计划科技创新领军人才
3. 2024年度，中国自动化学会自然科学二等奖：超大规模时变图表示学习理论与方法，罗辛（第一完成人）、李伟生、曾念寅、吴迪、王子栋。西南大学、重庆邮电大学、厦门大学
4. 2023-2024年度，国际期刊《IEEE Transactions on Neural Networks and Learning Systems》优秀编委奖
5. 2023年，国家网信优秀人才（首批，当年全国仅30人入选）
6. 2022年，国际期刊《IEEE Transactions on Neural Networks and Learning Systems》优秀编委奖
7. 2020年，国家高层次人才特殊支持计划青年拔尖人才
8. 2020年，科技部卓越期刊行动计划重点期刊《IEEE/CAA Journal of Automatica Sinica（自动化学报英文版）》优秀编委奖（每年仅2人入选）
9. 2019年度，重庆市自然科学一等奖：高维稀疏大数据智能分析理论与方法，罗辛（第一完成人）、李伟生、尚明生、曾念寅、夏云霓。中国科南宫娱乐
重庆绿色智能技术研究院、重庆邮电大学、厦门大学
10. 2019年，重庆市自然科学基金杰出青年基金
11. 2019年，重庆市青年专家工作室领衔专家
12. 2018年度，重庆市科技进步一等奖：智慧金融集成生物识别关键技术及应用，周曦、罗辛（第二完成人）、张小洪、李鹏华、李伟生、尚明生、肖斌、姚志强、王洪星、陈琳、周吉祥、李嫄源、朱智勤、周翔、温浩。重庆中科云丛科技有限公司、中国科南宫娱乐
重庆绿色智能技术研究院、重庆邮电大学、重庆大学、广州云从信息科技有限公司
13. 2018年度，中国人工智能学会吴文俊人工智能科技进步一等奖：智慧金融中的集成生物识别关键技术及应用，周曦、王国胤、罗辛（第三完成人）、李伟生、尚明生、肖斌、夏云霓、姚志强、周吉祥、周丽芳、袁野、吴全旺、周翔、胡峰、温浩。重庆中科云丛科技有限公司、重庆邮电大学、中国科南宫娱乐
重庆绿色智能技术研究院、重庆大学、广州云从信息科技有限公司
14. 2018年，中国科南宫娱乐
百人计划青年俊才（择优支持）
15. 2017年，重庆市市级创新创业示范团队：大数据智能计算创新团队带头人
16. 2017年，IEEE学会高级会员
17. 2017年，科技部卓越期刊行动计划重点期刊《IEEE/CAA Journal of Automatica Sinica（自动化学报英文版）》编委（AE）
18. 2017年，重庆市第三批高层次人才特殊支持计划青年拔尖人才
19. 2017年，大数据智能计算重庆市重点实验室执行主任
20. 2015年，ACM中国学术新星（重庆分会）奖
21. 2014年，SCI检索期刊《Frontiers of Computer Science in China》青年编委，2014年获评优秀青年编委
【担任编委情况】
1. 国际期刊IEEE Transactions on Neural Networks and Learning Systems（中科院SCI一区Top，IF=10.4）编委
2. 科技部卓越期刊行动计划重点期刊IEEE/CAA Journal of Automatica Sinica（中科院SCI一区Top，IF=11.8）编委
3. 国际学术期刊Neurocomputing（中科院SCI二区Top，IF 5.779）编委
4. 国际学术期刊Frontiers in Neurorobotics（中科院SCI三区，IF 3.493）编委
【学生培养】
培养/联合培养博士毕业生9名，全部在高校/科研院所工作：吴迪/袁野/吴昊工作于西南大学、任教授/副教授，李蔚凌工作于东莞理工南宫娱乐
计算机南宫娱乐
、任副院长；陈敏治工作于重庆理工大学、任准聘副教授；秦雯工作于四川师范大学、任准聘副教授；李志斌于中科院新疆理化所任特别研究助理；钟裕荣、刘志刚于电子科技大学做博士后。目前指导在读博士9名，按照“需求牵引、理论导引、强化创新”的培养理念，在申请人指导下已发表IEEE汇刊论文37篇。
