张鹏 广州大学

人工智能算法研究

• 数据流智能算法研究： 面向实时数据流建立轻量级的在线机器学习算法，包括基于active learning的流采样算法，基于ensemble variance reduction的多模型权重优化算法，基于frequent pattern的流频繁项挖掘算法，基于Piecewise passive-aggressive的模型权重优化算法，成果获得国家基金委青年基金项目（NSFC 61003167），面上基金（NSFC 61370025）等项目支持。

• 图数据智能算法研究： 面向大规模网络图数据，开发网络图的结点特征学习模型，包括基于feature aggregation的深度特征学习，基于network diffusion 的动态特征学习，基于subgraph的团伙特征学习，模型应用在网络青少年欺凌检测、网络影响力分析、网络推荐等项目中，获得澳大利亚研究委员会的基金支持，并获得国际计算科学(ICCS-14)最佳论文奖Best Paper Award。

网络安全和反欺诈算法研究

• 金融反欺诈和隐私计算：将人工智能技术引入网络支付反洗钱，对百亿级别交易进行快速反洗钱审查，获得多项金融风控模型专利；并在人工智能平台上开发通用算法组件，主要是特征学习算法，通过特征嵌入（embedding）提升金融反欺诈模型AUC表现，场景覆盖支付、保险和信用等多场景；基于联邦学习，实现基于多方联合的用户信用评估模型。

• 电商反欺诈模型：负责基于图在线计算的电商直播风控模型，采用动态异构图神经网络模型发现直播虚假交易，实现了对大型网络直播平台500多万买家，10多万网红主播，百万件商品上快速建模分析，成果发表在多个CCF A类会议和SCI期刊上。

中国计算机学会 CCF A/B类期刊论文（+SCI期刊）

• Yang Gao, Peng Zhang, Chuan Zhou, Hong Yang, Zhao Li, Yue Hu, and Yu S. Philip. HGNAS++: efficient architecture search for heterogeneous graph neural networks. IEEE Trans. on Knowledge and Data Engineering (TKDE), DOI: 10.1109/TKDE.2023.3239842, 2023. (CCF A类期刊)

• Yang Gao, Peng Zhang, Hong Yang, Chuan Zhou, Zhao Li, Zhihong Tian, Yue Hu, Jingren Zhou, GraphNAS++: Distributed Architecture Search for Graph Neural Networks, IEEE Trans. on Knowledge and Data Engineering (TKDE), DIO: 10.1109/TKDE.2022.3178153, 2022.(CCF A类期刊)

• Xixiun Lin, Zhao Li, Peng Zhang, Luchen Liu, Chuan Zhou, Bing Wang, Zhihong Tian, Structure-Aware Prototypical Neural Process for Few-Shot Graph Classification, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Accepted, 10.1109/TNNLS.2022.3173318, 2022.(SCI一区期刊)

• Hong Yang, Ling Chen, Shirui Pan, Haishuai Wang, Peng Zhang, Discrete embedding for attributed graphs, Pattern Recognition, Vol.123, 2022. (CCF B类期刊)

• Hong Yang, Peng Zhang, Haishuai Wang, Chuan Zhou, Zhao Li, Li Gao, Qingfeng Tan，Towards embedding information diffusion data for understanding big dynamic networks, Neurocomputing, Vol. 466, pages: 265-284, 2021. (SCI二区期刊)

• Yifan He, Zhao Li, Lei Fu, Anhui Wang, Peng Zhang, Shuigeng Zhou, Ji Zhang, Ting Yu, TARA-Net: A Fusion Network for Detecting Takeaway Rider Accidents, ACM Transactions on Intelligent Systems and Technology, Volume 12(6), pp 1–19， 2021. (SCI期刊）

• Qin Zhang, Jia Wu, Peng Zhang, Guodong Long and Chengqi Zhang, Salient Subsequence Learning for Time Series Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 41(9), pages: 2193–2207, 2019.(CCF A类期刊)

• Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Tsang, Chengqi Zhang and Wu Xindong, Incremental subgraph feature selection for graph classification, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 29(1), pages: 128–142, 2017. (CCF A类期刊)

• Qin Zhang, Peng Zhang, Guodong Long, Wei Ding, Chengqi Zhang and Xingdong Wu, Online Learning from Trapezoidal Data Streams, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 28(10), pages: 2709–2723, 2016. (CCF A类期刊)

• Peng Zhang*, Chuan Zhou, Peng Wang, Byron Gao, Xingquan Zhu, E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams, IEEE Transactions on Knowledge and Data Engineering(TKDE), Vol. 27(2), pages: 461–474, 2015. (CCF A类期刊)

• Chuan Zhou, Peng Zhang, Wenyu Zang, Li Guo, On the Upper Bounds of Spread for Greedy Algorithms in Social Network Influence Maximization. IEEE Trans. on Knowledge and Data Engineering(TKDE), Vol. 27(10), pages: 2770-2783, 2015. (CCF A类期刊)

• Yong Shi, Jianyu Miao, Zhengyu Wang, Peng Zhang and Lingfeng Niu, Feature Selection With $L_{2, 1-2}$ Regularization, IEEE Transactions on Neural Networks and Learning Systems(TNNLS), Vol.29(10), pages: 4967–4982, 2018. (CCF A类期刊)

• Zhiquan Qi, Meng Fan, Yingjie Tian, Yong Shi, Peng Zhang, Adaboost-LLP: a boosting method for learning with label proportions, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Vol. 29(8), pages:3548–3559, 2018.(CCF A类期刊)

• Jingjing Tang, Yingjie Tian, Peng Zhang and Xiaohui Liu, Multiview privileged support vector machines, IEEE Transactions on Neural Networks and Learning Systems(TNNLS), Vol. 29(8), pages: 3463–3477, 2018. (CCF A类期刊)

• Rongrong Ma, Lingfeng Niu, Peng Zhang, Transformed L1 Regularization for Learning Sparse Deep Neural Networks, Neural Networks, Vol.119, pages: 286–298, 2019. (CCF B类期刊)

• Lin Cui, Jia Wu, Dechang Pi, Peng Zhang, and Paul Kennedy, Dual Implicit Mining-Based Latent Friend Recommendation, IEEE Transactions on Cybernetics, 2018. (CCF B类期刊)

• Lingfeng Niu, Ruizhi Zhou, Yingjie Tian, Zhiquan Qi, and Peng Zhang, Nonsmooth Penalized Clustering via $l_p$ Regularized Sparse Regression, IEEE Transactions on Cybernetics, Vol. 47 (6), pages: 1423–1433, 2017. (CCF B类期刊)

• Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active learning from stream data using optimal weight classifier ensemble, IEEE Transactions on Cybernetics, Vol. 40(6), pages: 1607–1621, 2010. (CCF B类期刊)

• Peng Zhang*, Jing He, Guodong Long, Guangyan Huang, and Chengqi Zhang, Towards anomalous diffusion sources detection in a large network, ACM Transactions on Internet Technology, Vol. 16(1), pages: 2–36, 2016. (CCF B类期刊)

• Jia Wu, Shirui Pan, Xingquan Zhu, Peng Zhang, Chengqi Zhang, Self-adaptive one-dependence estimators for classification, Pattern Recognition, Vol. 51, pages: 358–377, 2016. (CCF B类期刊)

• Yongshan Zhang, Jia Wu, Zhihua Cai, Peng Zhang, Chengqi Zhang and Ling Chen, Memetic extreme learning machine, Pattern Recognition, Vol. 58, pages: 135–148, 2016. (CCF B类期刊)

• Qinzhe Zhang, Jia Wu, Qin Zhang, Peng Zhang, Guodong Long, Chengqi Zhang, Dual influence embedded social recommendation, World Wide Web Journal, pages: 1–26, 2017. (CCF B类期刊)

• Peng Wang, Peng Zhang*, Chuan Zhou, Zhao Li, Hong Yang, Hierarchical evolving Dirichlet processes for modeling nonlinear evolutionary traces in temporal data, Data Mining and Knowledge Discovery, Vol. 31, pages: 32–64, 2017. (CCF B类期刊)

• Haishuai Wang, Jia Wu, Shirui Pan, Peng Zhang, Ling Chen, Towards large-scale social networks with online diffusion provenance detection, Computer Networks, Vol.114, 154–166, 2017. (CCF B类期刊)

• Peng Zhang*, Byron J Gao, Ping Liu, Yong Shi, Li Guo, A framework for application-driven classification of data streams, Neurocomputing, Vol. 92, pages: 170-182, 2012. (SCI二区期刊)

• Peng Zhang*, Xingquan Zhu, Yong Shi, Li Guo, Xindong Wu, Robust ensemble learning for mining noisy data streams, Decision Support Systems, VOl. 50(2), pages: 469-479, 2011. (SCI二区期刊)

中国计算机学会 CCF A/B类会议论文

• Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu, Weiqiang Wang, Multi-Aspect Heterogeneous Graph Augmentation, Proceedings of the ACM Web Conference (WWW-23), 2023. (CCF A类)

• Qin Zhang, Qincai Li, Xiaojun Chen, Peng Zhang, Shirui Pan, Philippe Fournier-Viger, Joshua Zhexue Huang, A Dynamic Variational Framework for Open-World Node Classification in Structured Sequences, IEEE International Conference on Data Mining (ICDM-22), 2022. (CCF B类)

• Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, and Bin Wang. Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences. In Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM-21), pages: 360-369. 2021. (CCF B类)

• Haishuai Wang, Zhao Li, Xuanwu Liu, Donghui Ding, Zehong Hu, Peng Zhang, Chuan Zhou, and Jiajun Bu. Fulfillment-Time-Aware Personalized Ranking for On-Demand Food Recommendation. In Proc. of the 30th ACM International Conference on Information & Knowledge Management (CIKM-21), pages: 4184-4192. 2021. (CCF B类)

• Zhao Li, Haishuai Wang, Peng Zhang*, Pengrui Hui, Jiaming Huang, Jian Liao, Ji Zhang, Jianjun Bu. Live-Streaming Fraud Detection: A Heterogeneous Graph Neural Network Approach, In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-21), pages: 3670–3678, 2021. (CCF A类)

• Huyi Li, Zhihong Chen, Chenliang Li, Rong Xiao, Hongbo Deng, Peng Zhang, Yongchao Liu, Hailong Tang, Path-based Deep Network for Candidate Item Matching in Recommenders. In Proc. of the 44th International ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR-21), pages: 1493-1502, 2021. (CCF A类)

• Tengfei Liu, Jianliang Gao, Ling Tian, Zhao Li, Peng Zhang, and Ji Zhang. MDNN: A Multimodal Deep Neural Network for Predicting Drug-Drug Interaction Events. Proc. of the 30th International Joint Conferences on Artificial Intelligence (IJCAI-21), pages: 3536-3542, 2021. (CCF A类)

• Gao Yang, Peng Zhang*, Zhao Li, Chuan Zhou, Yongchao Liu, and Yue Hu. Heterogeneous Graph Neural Architecture Search. In Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM-21), pages: 1066-1071. 2021. (CCF B类)

• Li Zhao, Pengcheng Zou, Xia Chen, Shichang Hu, Peng Zhang, Yumou Zhang, Bingsheng He, Yuchen Li, and Xing Tang. From community search to community understanding: A multimodal community query engine. In Proc. of the ACM International Conference on Information & Knowledge Management (CIKM-21), pages: 4749-4753. 2021. (CCF B类)

• Xia Wei, Fei Zhao, Haishuai Wang, Peng Zhang, Anhui Wang, and Kang Li. Crawler Detection in Location-Based Services Using Attributed Action Net. In Proc. of the 30th ACM International Conference on Information & Knowledge Management (CIKM-21), pages: 4234-4242. 2021. (CCF B类)

• Yang Gao, Hong Yang, Peng Zhang, Chuan Zhou, Yue Hu, Graph Neural Architecture Search, Proceedings of the 29th International Joint Conferences on Artificial Intelligence (IJCAI-20), page: 1403-1409, 2020. (CCF A类)

• Hong Yang, Ling Chen, Meilong Lei, Lingfeng Niu, Chuan Zhou, Peng Zhang. Discrete Embedding for Latent Networks, Proc. of the 29th International Joint Conferences on Artificial Intelligence (IJCAI-20), pages: 1223-1229, 2020. (CCF A类)

• Hong Yang, Shirui Pan, Ling Chen, Chuan Zhou, Peng Zhang, Low-Bit Quantization for Attributed Network Representation Learning. Proc. of the 28th International Joint Conferences on Artificial Intelligence (IJCAI-19), pages: 4047-4053, 2019. (CCF A类)

• Hong Yang, Shirui Pan, Peng Zhang, Chengqi Zhang, Binarized Attributed Network Embedding, Proc. of the IEEE International Conference on Data Mining (ICDM-18), pages: 1476-1481, 2018. (CCF B类)

• Qin Zhang, Peng Zhang, Guodong Long, Chengqi Zhang, Xindong Wu, Towards Mining Trapezoidal Data Streams. Proceedings of the IEEE International Conference on Data Mining (ICDM-16), 2016. (CCF B类)

• Chuan Zhou, Weixue Lu, Peng Zhang, Jia Wu, and Li Guo, On the Minimum Differentially Resolving Set Problem for Diffusion Source Inference in Networks. In Proc. of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), 2016. (CCF A类)

• Jia Wu, Shirui Pan, Peng Zhang and Xingquan Zhu, Direct Discriminative Bag Mapping for Multi-Instance Learning. Proc. of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), 2016. (CCF A类)

• Weiwei Feng, Peng Wang, Chuan Zhou, Peng Zhang, Li Guo. Fast Search for Distance Dependent Chinese Restaurant Processes. In Proceedings of the 24rd International World Wide Web Conference (WWW-15), 2015. (CCF A类)

• Peng Wang, Peng Zhang, Chuan Zhou, Weiwei Feng, Li Guo, Modeling Infinite Topics on Social Behavior Data with Spatio-temporal Dependence, In Proceedings of ACM Conf. on Information and Knowledge Management (CIKM-15), 2015. (CCF B类)

• Wenyu Zang, Peng Zhang, Chuan Zhou, and Li Guo, Topic-aware Source Locating in Social Networks. In Proceedings of the 24rd International World Wide Web Conference (WWW-15), 2015. (CCF A类)

• Zhi Qiao, Peng Zhang, Chuan Zhou and Li Guo, Online Event Recommendation for Event-based Social Networks, In Proceedings of the 24rd International World Wide Web Conference (WWW-15), 2015. (CCF A类)

• Lu, Wei-Xue, Peng Zhang, Chuan Zhou, Chunyi Liu, and Li Gao. Influence maximization in big networks: an incremental algorithm for streaming subgraph influence spread estimation. In Proceedings of the 24 International Joint Conference on Artificial Intelligence (IJCAI-15), 2015. (CCF A类)

• Haishuai Wang, Peng Zhang, Ling Chen, Ivor Tsang, Chengqi Zhang, Defragging Subgraph Features for Graph Classification, In Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM-15), 2015. (CCF B类)

• Qiao Zhi, Peng Zhang, Wenjia Niu, Chuan Zhou, Li Guo. Online Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction. In Proceedings of the IEEE International Conference on Data Mining (ICDM-14) , 2014. (CCF B类)

• Qiao Zhi, Peng Zhang, Chuan Zhou, Li Guo and Binxing Fang, Combining Heterogenous Social and Geographical Information for Event Recommendation. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), 2014. (CCF A类)

• Qiao Zhi, Peng Zhang, Chuan Zhou, Yanan Cao, Li Guo, Yanchuan Zhang, Event Recommendation in Event-Based Social Networks. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), 2014. (CCF A类)

• Chuan Zhou, Peng Zhang, Wenyu Zang and Li Guo. Maximizing the Long-term Integral Influence in Social Networks under the Voter Model. In Proceedings of the 23rd ACM International World Wide Web Conference (WWW-14), 2014. (CCF A类)

• Chuan Zhou, Peng Zhang, Jing Guo and Li Guo. Upper Bound based Greedy Algorithm for Mining Top-k Influential Nodes in Social Networks. In Proceedings of the 23rd ACM International World Wide Web Conference (WWW-14), 2014. (CCF A类)

• Zhi Qiao, Peng Zhang, Jing He, Yanan Cao, Chuan Zhou and Li Guo. Combining Geographical Information of Users and Content of Items for Accurate Rating Prediction. In Proc. of ACM Int. World Wide Web Conference (WWW-14)，2014. (CCF A类)

• Jing Guo, Peng Zhang, Chuan Zhou, Yanan Cao, Li Guo. Item-Based Top- k Influential User Discovery in Social Networks. In Proceedings of the IEEE International Conference on Data Mining (ICDM-13), 2013. (CCF B类)

• Chuan Zhou, Peng Zhang, Jing Guo, Xingquan Zhu and Li Guo, UBLF: An upper bound based approach to discover influential nodes in social networks. In Proc. of the IEEE International Conference on Data Mining (ICDM-13), 2013. (CCF B类)

• Jun Li, Peng Zhang, Yanan Cao, Ping Liu, and Li Guo. Efficient Behavior Targeting Using Ensmeble SVM Indexing. In Proceedings of the IEEE International Conference on Data Mining (ICDM-12). (CCF B类)

• Peng Wang, Peng Zhang, and Li Guo. Minining Multi-label Data Streams Using Ensemble-based Active Learning. In Proceedings of the SIAM Int. Conference on Data Mining (SDM-12), 2012. (CCF B类)

• Peng Zhang, Jun Li, Peng Wang, Byron Gao, Xingquan Zhu, and Li Guo, Enabling Fast Prediction for Ensemble Models on Data Streams. In Proc. of the 17th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD-11), 2011. (CCF A类)

• Jing Guo, Peng Zhang, Jianlong Tan, and Li Guo, Mining Frequent Patterns across Multiple Data Streams. In Proceedings of ACM Conf. on Information and Knowledge Management (CIKM-11), 2011. (CCF B类)

• Jun Li, Peng Zhang, Jianlong Tan,Ping Liu, and Li Guo, Continuous Data Stream Query in the Cloud. In Proceedings of ACM Conf. on Information and Knowledge Management (CIKM-11), 2011. (CCF B类)

• Peng Zhang, Xingquan Zhu, Jianlong Tan, and Li Guo, SKIF: A Data Imputation Framework for Concept Drifting Data Streams, In Proceedings of ACM Conf. on Information and Knowledge Management (CIKM-10), 2010. (CCF B类)

• Peng Zhang, Xingquan Zhu, Jianlong Tan, and Li Guo. Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams. In Proceedings of the IEEE International Conference on Data Mining (ICDM-10), 2010. (CCF B类)

• Peng Zhang, Xingquan Zhu, and Li Guo. Mining Data Streams with Labeled and Unlabeled Training Examples. In Proceedings of the IEEE International Conference on Data Mining (ICDM-09), 2009. (CCF B类)

• Xiaofei Zhou, Wenhan Jiang, Yingjie Tian, Peng Zhang, Guangli Nie, and Yong Shi. A New Kernel-based Classification Algorithm. In Proceedings of the IEEE International Conference on Data Mining (ICDM-09), 2009. (CCF B类)

• Peng Zhang, Xingquan Zhu, and Yong Shi, Categorizing and Mining Concept Drifting Data Streams. In Proceedings of the 14th ACM international conference on Knowledge Discovery and Data mining (KDD-08), 2008. (CCF A类)

• Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, and Yong Shi. Cleansing Noisy Data Streams. In Proceedings of the IEEE International Conference on Data Mining (ICDM-08), 2008. (CCF B类)

联系方式 (Contacts)

地址：广州市黄埔区海丝知识中心B3栋
Addr: #B3, Hai-si Knowledge Center, Huangpu district, Guangzhou, China.

E-mail: p.zhang At gzhu.edu.cn

Phone: ## (Office)