白璐 博士，教授，博士生导师，国家优青，国家优秀自费留学生奖，龙马学者青年学者
基本资料：
白璐，男，副教授，博士生导师，国家优秀青年科学基金获得者（国家优青），国家优秀自费留学生奖学金获得者（教育部批准，2014年度全球500人，英国使馆区35人），彩乐仑彩票首批“龙马学者青年学者”。2015年1月于英国约克大学（University of York, UK）取得博士学位，导师：Edwin R. Hancock教授（IEEE/IAPR Fellow, IAPR前副主席）。于澳门科技大学（Macau University of Science and Technology, Macau SAR, China）分别获理学学士（优秀毕业论文）、理学硕士学位。现任职于彩乐仑彩票计算机系、国家金融安全教育部工程研究中心。主要研究方向为：基于图的模式识别、机器学习、量子游走、金融数据分析。主持国家自然科学基金优秀青年、面上、青年项目3项，模式识别国家重点实验室开放课题项目1项（结题评优），彩乐仑彩票第四批青年科研创新团队项目与标志性科研成果预培项目2项。发表国际权威期刊会议论文近90篇（CCF/CAA推荐近60篇，IAPR旗下会议20余篇），其中代表性第一/通讯作者国际顶级期刊、会议TPAMI、TKDE、TNNLS、TCYB、PR、ICML、IJCAI、ECML-PKDD、ICDM论文22篇（CCF/CAA推荐A类19篇）。部分研究成果已应用于科大讯飞、中国电信等知名企业实际业务。担任国际模式识别期刊Pattern Recognition副主编（Associate Editor），并作为责任客座编辑（Managing Guest Editor）于该期刊组织该期刊首个“基于图方法的金融大数据分析特刊”，担任IJCAI 2020 Session Chair (FinTech Track)，ICPR 2018 Session Chair。曾获三项国际会议最佳/优秀论文奖（ICIAP 2015，ICPR 2018，IEEM 2019），以及国际模式识别学会IAPR Newsletter下一代（The Next Generation）专栏报道。 指导本科/硕士生多人获校级优秀毕业论文、北京市优秀毕业生，指导学生以第一或主要作者发表国际顶级或重要期刊会议论文多篇。
工作经历：
[1] 2017年11月 – 今：副教授（破格），博士生导师（破格），彩乐仑彩票-计算机系/国家金融安全教育部工程研究中心
[2] 2015年07月 – 2017年10月：讲师，彩乐仑彩票-计算机系
[3] 2015年02月 – 2015年06月：讲师（实习），彩乐仑彩票-计算机系
主要讲授课程：
数据结构、大学物理、算法导论
学术兼职：
[1] 2021年02月 – 今：副主编（Associate Editor），期刊Pattern Recognition (PR, IF: 7.47, CAA-A, 中财AAA)
[2] 2019年11月 – 今：中国自动化学会，模式识别与机器智能专委会，委员
[3] 2019年11月 – 今：中国图象图形学会，视觉大数据专委会，委员
社会兼职：
[1] 2020年07月 – 今：理事，北京市海淀区统战部知联会
[2] 2018年12月 – 今：常务理事，彩乐仑彩票欧美同学会
主持项目：
[1] 国家自然科学基金，优秀青年科学基金项目，《结构模式识别与金融股市风险分析》，2022年01月 – 2024年12月，200万，在研，项目负责人
[2] 国家自然科学基金，面上项目，《基于深度图卷积网络的金融风险分析》，2020年01月 – 2023年12月，61万，在研，项目负责人
[3] 国家自然科学基金，青年科学基金项目，《基于图核函数的机器学习算法及其在金融分析理论的研究》，2016年01月 – 2018年12月，22万，结题，项目负责人
[4] 彩乐仑彩票，第四批青年科研创新团队，2017年04月 – 2020年04月，30万，结题，项目负责人
[5] 模式识别国家重点实验室，开放课题项目，2016年01月 – 2017年12月，4万，结题评优，项目负责人
代表性学术成果（截至2021年8月,*为通讯作者）：
在投论文
[1] Lixin Cui, Lu Bai* (Correspondence), Xiao Bai, Yue Wang, Edwin R. Hancock: submitted to IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Major Revision. (CAA-A类，中科院一区Top)
部分代表性期刊论文
[1] Lu Bai, Lixin Cui*, Yuhang Jiao, Luca Rossi, Edwin R. Hancock: Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Online. (CCF-A，CAA-A，中科院一区Top)
[2] Lu Bai, Yuhang Jiao, Lixin Cui*, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock: Learning Graph Convolutional Networks based on Quantum Vertex Information Propagation. IEEE Transactions on Knowledge and Data Engineering (TKDE), Online. (CCF-A，CAA-A，中科院一区Top)
[3] Lu Bai, Lixin Cui, Zhihong Zhang*, Lixiang Xu, Yue Wang, Edwin R. Hancock: Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Online. (CAA-A，中科院一区Top)
[4] Zhihong Zhang, Dongdong Chen, Lu Bai* (Correspondence), Jianjia Wang and Edwin R Hancock: Graph Motif Entropy for Understanding Time-Evolving Networks, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Online. (CAA-A，中科院一区Top)
[5] Lu Bai, Luca Rossi*, Lixin Cui*, Jian Cheng, Edwin R. Hancock: A Quantum-Inspired Similarity Measure for the Analysis of Complete Weighted Graphs. IEEE Transactions on Cybernetics (TCYB), 50(3): 1264-1277, 2020. (CAA-A，中科院一区Top)
[6] Lu Bai*, Edwin R. Hancock: Fast depth-based Subgraph Kernels for Unattributed Graphs. Pattern Recognition (PR), 50: 233-245, 2016. (CAA-A，中科院一区Top)
[7] Lu Bai*, Francisco Escolano, Edwin R. Hancock: Depth-based Hypergraph Complexity Traces from Directed Line Graphs. Pattern Recognition (PR), 54: 229-240, 2016. (CAA-A，中科院一区Top)
[8] Lu Bai*, Luca Rossi*, Andrea Torsello, Edwin R. Hancock: A Quantum Jensen-Shannon Graph Kernel for Unattributed Graphs. Pattern Recognition (PR), 48(2): 344-355, 2015. (CAA-A，中科院一区Top)
[9] Lu Bai*, Edwin R. Hancock: Depth-based Complexity Traces of Graphs. Pattern Recognition (PR), 47(3): 1172-1186, 2014. (CAA-A，中科院一区Top)
[10] Lixin Cui, Lu Bai* (Correspondence), Yue Wang, Philip S. Yu, Edwin R. Hancock: Fused Lasso for Feature Selection using Structural Information. Pattern Recognition (PR) 119: 108058, 2021. (CAA-A，中科院一区Top)
[11] Lixin Cui, Lu Bai* (Correspondence), Yanchao Wang, Xin Jin, Edwin R. Hancock: Internet Financing Credit Risk Evaluation Using Multiple Structural Interacting Elastic Net Feature Selection. Pattern Recognition (PR) 114: 107835, 2021. (CAA-A，中科院一区Top)
[12] Lixiang Xu, Lu Bai* (Correspondence), Xiaoyi Jiang, Ming Tan, Daoqiang Zhang, Bin Luo: Deep Rényi Entropy Graph Kernel. Pattern Recognition (PR) 111: 107668, 2021. (CAA-A，中科院一区Top)
[13] Zhihong Zhang, Yangbin Zeng, Lu Bai* (Correspondence), Yiqun Hu, Meihong Wu, Shuai Wang, Edwin R. Hancock: Spectral bounding: Strictly Satisfying the 1-Lipschitz Property for Generative Adversarial Networks. Pattern Recognition (PR) 105: 107179, 2020. (CAA-A，中科院一区Top)
[14] Lixiang Xu, Xiaofeng Wang, Lu Bai* (Correspondence), Jin Xiao*, Qi Liu, Enhong Chen, Xiaoyi Jiang, Bin Luo: Probabilistic SVM Classifier Ensemble Selection Based on GMDH-type Neural Network. Pattern Recognition (PR) 106: 107373, 2020. (CAA-A，中科院一区Top)
[15] Zhihong Zhang, Dongdong Chen, Jianjia Wang, Lu Bai* (Correspondence), Edwin R. Hancock: Quantum-based Subgraph Convolutional Neural Networks. Pattern Recognition (PR) 88: 38-49, 2019. (CAA-A，中科院一区Top)
[16] Zhihong Zhang, Lu Bai*(Correspondence), Yuanheng Liang, Edwin R. Hancock: Joint Hypergraph Learning and Sparse Regression for Feature Selection. Pattern Recognition (PR) 63: 291-309, 2017. (CAA-A，中科院一区Top)
[17] Lu Bai, Lixin Cui*, Xiao Bai, Edwin R. Hancock: Deep Depth-based Representations of Graphs Through Deep Learning Networks. Neurocomputing 336: 3-12, 2019. (CAA-B，中科院二区)
[18] Lixin Cui, Lu Bai* (Correspondence), Zhihong Zhang, Yue Wang, Edwin R. Hancock: Identifying the Most Informative Features Using A Structurally Interacting Elastic net. Neurocomputing 336: 13-26, 2019. (CAA-B，中科院二区)
[19] Lu Bai, Lixin Cui*, Luca Rossi, Lixiang Xu, Xiao Bai, Edwin R. Hancock: Local-global Nested Graph Kernels Using Nested Complexity Traces. Pattern Recognition Letters 134: 87-95, 2020. (CCF-C，中科院三区)
[20] Lu Bai, Luca Rossi, Lixin Cui, Zhihong Zhang*, Peng Ren, Xiao Bai, Edwin R. Hancock: Quantum Kernels for Unattributed Graphs Using Discrete-time Quantum Walks. Pattern Recognition Letters 87: 96-103, 2017. (CCF-C，中科院三区)
[21] Zhihong Zhang, Yiyang Tian, Lu Bai* (Correspondence), Jianbing Xiahou, Edwin R. Hancock: High-order Covariate Interacted Lasso for Feature Selection. Pattern Recognition Letters 87: 139-146, 2017. (CCF-C，中科院三区)
[22] Lu Bai, Edwin R. Hancock: Graph Kernels from the Jensen-Shannon Divergence. Journal of Mathematical Imaging and Vision (JMIV) 47(1-2): 60-69, 2013.
部分代表性会议论文
[23] Lu Bai, Lixin Cui*, Yue Wang, Edwin R. Hancock: A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2020. (CCF-A)
[24] Lu Bai, Luca Rossi, Zhihong Zhang*, Edwin R. Hancock: An Aligned Subtree Kernel for Weighted Graphs. Proceedings of International Conference on Machine Learning (ICML), 2015: 30-39. (CCF-A)
[25] Lu Bai, Zhihong Zhang*, Chaoyan Wang, Xiao Bai, Edwin R. Hancock: A Graph Kernel Based on the Jensen-Shannon Representation Alignment. Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2015: 3322-3328. (CCF-A)
[26] Lu Bai, Yuhang Jiao, Lixin Cui*, Edwin R. Hancock: Learning Aligned-Spatial Graph Convolutional Networks for Graph Classification. Proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD) 1: 464-482, 2019. (CCF-B)
[27] Yue Wang, Yao Wan, Chenwei Zhang, Lu Bai* (Correspondence), Lixin Cui, Philip S. Yu: Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking. Proceedings of International Conference on Data Mining (ICDM), 1366-1371, 2019. (CCF-B)
[28] Lu Bai, Luca Rossi, Horst Bunke, Edwin R. Hancock: Attributed Graph Kernels Using the Jensen-Tsallis q-Differences. Proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD) 1: 99-114, 2014. (CCF-B)
[29] Yibo Chai, Yahu Cong, Lu Bai* (Correspondence), Lixin Cui: Loan Recommendation in P2P Lending Investment Networks: A Hybrid Graph Convolution Approach. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 945-949, 2019.（最佳论文提名，优秀论文奖，约<8/1200）
[30] Chuanyu Xu, Dong Wang, Zhihong Zhang*, Beizhan Wang, Da Zhou, Guijun Ren, Lu Bai, Lixin Cui, Edwin R. Hancock: Depth-based Subgraph Convolutional Neural Networks. Proceedings of International Conference on Pattern Recognition (ICPR), 1024-1029, 2018. (CCF-C)（最佳Pattern Recognition and Machine Learning Track论文奖，6/1258）
[31] Lu Bai, Zhihong Zhang, Peng Ren, Luca Rossi, Edwin R. Hancock: An Edge-Based Matching Kernel Through Discrete-Time Quantum Walks. International Conference on Image Analysis and Processing (ICIAP) 1: 27-38, 2015.（最佳学生论文奖，1/234）
联系方式:
bailucs@cufe.edu.cn
