教授、博士生导师、副院长，“湖南省芙蓉学者奖励计划”青年学者、湖南省青年骨干教师、湖南科技大学高层次人才“学术带头人”。2011年6月博士毕业于武汉大学，2014年9月至12月在香港中文大学从事访问研究，2015年3月至2016年3月在美国阿肯色大学从事博士后工作。主要研究兴趣为服务计算与边缘计算、机器学习与推荐系统、智能化软件与服务。在IEEE TSC、IEEE TITS、IEEE TAI、IEEE TNSM、计算机学报、软件学报等国内外重要学术期刊以及ICWS、SCC等国际学术会议上发表论文160余篇，其中CCF 推荐的国际学术期刊与会议论文80余篇，中科院一区、CCF A类以及IEEE Trans系列期刊论文20余篇，荣获ICSS2022、NCSC2021、SCC2019等国际国内学术会议的最佳论文奖/最佳学生论文奖7次。在服务计算领域旗舰性国际学术会议ICWS上持续发表研究长文15篇。主持完成国家自然科学基金面上项目、国家重点研发计划子课题、国家自然科学基金青年项目各1项，省部级及其他项目10余项。获批软件著作权15项，申请/授权发明专利11项。主持获得湖南省高等教育教学成果奖一等奖1项，指导学生获得湖南省优秀硕士学位论文2篇、中国互联网+国赛铜奖/省赛金奖2项以及湖南省程序设计竞赛二等奖等省级以上奖项10余项。现为CCF高级会员、CCF服务计算专委会常务委员、CCF协同计算专委会委员，《International Journal of Cloud Computing》杂志编委，湖南省高教学会计算机教育专委会常务理事，湖南省大学计算机教指委委员，曾任国际服务计算学会中国青年学者论坛（SSYSF）副主席，YOCSEF长沙学术秘书、学术委员。协助或组织承办SCA2012/GCC2012、CCF NCSC2017/CBPM2017以及ChineseCSCW2021等国际学术会议/CCF学术年会3次，担任20余个国际国内学术会议的组织委员会主席、程序委员会委员以及多个学术期刊审稿人，荣获CCF会员发展优秀奖/SSYSF杰出服务奖。参编计算机科学前沿丛书·十讲系列—“服务计算十讲”。目前指导博士生4名，硕士生11名。

联系方式：bqcao@hnust.edu.cn; 13047225827

主持（完成）的部分科研项目：

[1] 国家自然科学基金面上项目, “机器学习增强的服务混搭开发方法研究” (61873316, 2019.1-2022.12，完成).

[2] 国家重点研发计划子课题, “服务需求和语义建模工具集研发” (2018YFB1402800-04, 2019.1-2022.12，完成).

[3] 国家自然科学基金青年项目, “云环境下的服务信任评估及组合优化研究” (61402168, 2015.1-2017.12，完成).

[4] 湖南省自然科学基金, “基于图神经网络的智能服务推荐方法研究” (2021JJ30274, 2021.1-2023.12，完成).

[5] 湖南省自然科学基金, “大数据环境下机器学习支持的服务挖掘方法研究” (2017JJ2098, 2018.1-2020.12，完成).

[6] 湖南省自然科学基金, “网络化软件按需服务中的高可信关键技术研究” (12JJB009, 2012.12-2014.12，完成).

[7] 软件工程国家重点实验室开放基金, “基于社会网络的软件服务可信评估及协同优化研究” (SKLSE2014-10-10, 2015.1-2016.12，完成).

[8] 网络与交换技术国家重点实验室开放基金, “基于机器学习的云服务网络挖掘方法研究” (SKLNST-2016-2-26, 2017.1-2018.12，完成).

发表的部分学术论文：

[1] Buqing Cao, Hongfan Ye, Jianxun Liu, Bing Tang, Zhi Tao, Shuiguang Deng. SMART: Cost-aware Service Migration Path Selection based on Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems, 05 April 2024, https://www.doi.org/10.1109/ TITS.2024.3378920.

[2] Buqing Cao, Mi Peng, Ziming Xie, Jianxun Liu, Hongfan Ye, Bing Li, Kenneth K. Fletcher. PRKG: Pre-Training Representation and Knowledge-Graph-Enhanced Web Service Recommendation for Mashup Creation. IEEE Transactions on Network and Service Management,  2024, 21(02): 1737-1749.

[3] Buqing Cao, Mi Peng, Lulu Zhang, Yueying Qing, Bing Tang, Guosheng Kang, Jianxun Liu. Web Service Recommendation via Integrating Heterogeneous Graph Attention Network Representation and FiBiNET Score Prediction. IEEE Transactions on Services Computing, 2023, 16(05): 3837-3850.

[4] Buqing Cao, Lulu Zhang, Mi Peng, Yueying Qing, Guosheng Kang, Jianxun Liu. Web Service Recommendation via Combining Bilinear Graph Representation and xDeepFM Quality Prediction. IEEE Transactions on Network and Service Management, 2023, 20(02): 1078-1092.

[5] Buqing Cao, Yueying Qing, Dong Zhou, Xiang Xie, Guosheng Kang, Jianxun Liu, Kenneth K. Fletcher. Web APIs Recommendation via Combining Adaptive Multi-channel Graph Representation and xDeepFM Quality Prediction. IEEE Transactions on Artificial Intelligence, 22 December 2023, https://doi.org/10.1109/TAI.2023.3345828.

[6] Bing Tang, Feiyan Guo, Buqing Cao, Mingdong Tang, Kuan-Ching Li. Cost-Aware Deployment of Microservices for IoT Applications in Mobile Edge Computing Environment. IEEE Transactions on Network and Service Management, 2023, 20(3): 3119-3134.

[7] Guosheng Kang, Linghang Ding, Jianxun Liu, Buqing Cao, Yu Xu. Web API Recommendation Based on Self-Attentional Neural Factorization Machines With Domain Interactions. IEEE Transactions on Network Science and Engineering, 2023, 10(6): 3953-3963.

[8] Wenyu Zhao, Dong Zhou, Buqing Cao, Kai Zhang, Jinjun Chen. Adversarial Modality Alignment Network for Cross-modal Molecule Retrieval. IEEE Transactions on Artificial Intelligence, 2023, 1-12, https://doi.org/10.1109/TAI.2023.3254518.

[9] Xiang Xie, Jianxun Liu, Buqing Cao, Mi Peng, Guosheng Kang, Yiping Wen, Kenneth K. Fletcher. A Services Classification Method Based on Heterogeneous Information Networks and Generative Adversarial Networks. International Journal of Web Service Research, 2023, 20(1): 1-17.

[10] Buqing Cao, Mi Peng, Yueying Qing, Jianxun Liu, Guosheng Kang, Bing Li, Kenneth K. Fletcher. Web API Recommendation via Combining Graph Attention Representation and Deep Factorization Machines Quality Prediction. Concurrency and Computation-Practice & Experience, 2022, 34(21).

[11] Buqing Cao, Weishi Zhong, Xiang Xie, Lulu Zhang, Yueying Qing. A Multi-modal Feature Fusion-based Approach for Mobile Application Classification and Recommendation. Journal of Internet Technology, 2022, 23(6): 1417-1427.

[12] Guosheng Kang, Jianxun Liu, Yong Xiao, Yingcheng Cao, Buqing Cao, Min Shi. Web Services Clustering via Exploring Unified Content and Structural Semantic Representation. IEEE Transactions on Network and Service Management, 2022, 19(4): 4082-4096.

[13] Guosheng Kang, Jianxun Liu, Yong Xiao, Buqing Cao, Yu Xu, Manliang Cao. Neural and Attentional Factorization Machine-Based Web API Recommendation for Mashup Development. IEEE Transactions on Network and Service Management, 2021, 18(4): 4183-4196.

[14] Yong Xiao, Jianxun Liu, Guosheng Kang, Buqing Cao. LDNM: A General Web Service Classification Framework via Deep Fusion of Structured and Unstructured Features. IEEE Transactions on Network and Service Management, 2021, 18(3): 3858-3872.

[15] Buqing Cao, Xiaoqing (Frank) Liu, MD Mahfuzer Rahman, Bing Li, Jianxun Liu, Mingdong Tang. Integrated Content and Network-Based Service Clustering and Web APIs Recommendation for Mashup Development. IEEE Transactions on Services Computing, 2020, 13(1): 99-113.

[16] Buqing Cao, Junjie Chen, Jianxun Liu, Yiping Wen. A Topic Attention Mechanism and Factorization Machines based Mobile Application Recommendation Method. Mobile Networks and Application, 2020, 25(4): 1208-1219.

[17] Buqing Cao, Jianxun Liu, Yiping Wen, Hongtao Li, Qiaoxiang Xiao, Jinjun Chen.QoS-aware Service Recommendation Based on Relational Topic Model and Factorization Machines for IoT Mashup Applications. Journal of Parallel and Distributed Computing, 2019, 132: 177-189.

[18] Buqing Cao, Xiaoqing (Frank) Liu, Jianxun Liu, Mingdong Tang. Domain-aware Mashup Service Clustering based on LDA Topic Model from Multiple Data Sources. Information and Software Technology, 2017, 90: 40-54.

[19] Guosheng Kang, Mingdong Tang, Jianxun Liu, Xiaoqing Frank Liu, Buqing Cao. Diversifying Web Service Recommendation Results via Exploring Service Usage History. IEEE Transactions on Service Computing, 2016, 9(4): 566-579.

[20] Guosheng Kang, Jianxun Liu,Mingdong Tang, Buqing Cao, Yu Xu. An Effective Web Service Ranking Method via Exploring User Behavior. IEEE Transactions on Network and Service Management, 2015, 12(4): 554-564.

[21] Buqing Cao, Jianxun Liu, Mingdong Tang, Zibin Zheng, Guangrong Wang. Mashup Service Recommendation Based on Usage History and Service Network. International Journal of Web Service Research, 2013,10(4):82-101.

[22] Buqing Cao, Jianxun Liu, Xiaoqing Liu, Bing Li, Dong Zhou, Guosheng Kang. CHC-TSCM: A Trustworthy Service Composition Method based on an Improved CHC Genetic Algorithm. China Communications, 2013, 10(12): 77-91.

[23] Qian Peng, Buqing Cao, Xiang Xie, Shanpeng Liu, Guosheng Kang, Jianxun Liu. TH-SLP: Web Service Link Prediction Based on Topic-aware Heterogeneous Graph Neural Network. ICWS2023, pp. 465-474.

[24] Zilong Zeng, Buqing Cao, Hongfan Ye, Dong Zhou, Mingdong Tang, Feng Xiao. An Edge Server Co-deployment Method via Joint Optimization of Communication Delay and Load Balancing in Edge Collaborative Environment. CSCWD2023, pp. 207-212.

[25] Hao Huang, Buqing Cao, Shanpeng Liu, Dong Zhou, Mingdong Tang, Feng Xiao. A Web Service Classification Method Based on Graph Neural Network Knowledge Distillation. UIC2022, pp. 1710-1715.

[26] Ziming Xie, Buqing Cao, Xinwen Liyan, Bing Tang, Yueying Qing, Xiang Xie, Siyuan Wang. A Negative Sampling-Based Service Recommendation Method. CollaborateCom2022, pp. 3-19.

[27] Mi Peng, Buqing Cao, Junjie Chen, Guosheng Kang, Jianxun Liu, Yiping Wen. Heterogeneous Graph Attention Network- Enhanced Web Service Classification. ICWS2021, pp. 179-184.

[28] Xiangping Zhang, Jianxun Liu, Min Shi, Buqing Cao. Word Embedding-based Web Service Representations for Classification and Clustering. ICWS2021, pp. 34-43.

[29] Yong Xiao, Guosheng Kang, Jianxun Liu, Buqing Cao, Linghang Ding. WSGCN4SLP: Weighted Signed Graph Convolutional Network for Service Link Prediction. ICWS2021, pp. 135-144.

[30] Junjie Chen, Buqing Cao, Jianxun Liu, Bing Li. MR-UI: A Mobile Application Recommendation Based on User Interaction. ICWS2020, pp.134-141.

[31] Yong Xiao, Jianxun Liu, Guosheng Kang, Rong Hu, Buqing Cao, Yingcheng Cao, Min Shi. Structure Reinforcing and Attribute Weakening Network based API Recommendation Approach for Mashup Creation. ICWS2020, pp. 541-548.

[32] Guosheng Kang, Jianxun Liu, Buqing Cao, Manliang Cao. NAFM: Neural and Attentional Factorization Machine for Web API Recommendation. ICWS2020, pp. 330-337.

[33] Yingcheng Cao, Jianxun Liu, Min Shi, Buqing Cao, Xiangping Zhang, Yan Wang. Relationship Network Augmented Web Services Clustering. ICWS2019, pp. 247-254.

[34] Yingcheng Cao, Jianxun Liu, Min Shi, Buqing Cao, Ting Chen, Yiping Wen. Service Recommendation Based on Attentional Factorization Machine. SCC2019, pp.189-196.

[35] Min Shi, Jianxun Liu, Buqing Cao, Yiping Wen, Xiangping Zhang. A Prior Knowledge Based Approach to Improving Accuracy of Web Services Clustering. SCC2018, pp.1-8.

[36] Md Mahfuzer Rahman, Xiaoqing (Frank) Liu, Buqing Cao. Web API Recommendation for Mashup Development Using Matrix Factorization on Integrated Content and Network-Based Service Clustering. SCC2017, pp.225-232.

[37] Hongchao Li, Jianxun Liu, Buqing Cao, Mingdong Tang, Xiaoqing Frank Liu, Bing Li.Integrating Tag, Topic, Co-occurrence, and Popularity to Recommend Web APIs for Mashup Creation. SCC2017, pp. 84-91.

[38] Buqing Cao, Xiaoqing (Frank) Liu, Bing Li, Jianxun Liu, Mingdong Tang, Tingting Zhang, Min Shi.Mashup Service Clustering Based on an Integration of Service Content andNetwork via Exploiting a Two-Level Topic Model. ICWS2016, pp.212-219.

[39] 刘建勋, 丁领航, 康国胜, 曹步清, 肖勇. 基于特征深度融合的Web服务QoS联合预测. 通信学报, Vol. 43, No. 7, pp. 215-226, 2022.

[40] 肖勇, 刘建勋, 胡蓉, 曹步清, 曹应成. 基于GAT2VEC的Web服务分类方法. 软件学报, Vol. 32, No. 12, pp. 3751-3767, 2021.

[41] 曹步清, 肖巧翔, 张祥平, 刘建勋. 融合SOM 功能聚类与DeepFM质量预测的API 服务推荐方法. 计算机学报, Vol. 42, No. 6, pp. 1367-1383, 2019.

[42] 石敏, 刘建勋, 周栋, 曹步清, 文一凭. 基于多重关系主题模型的Web服务聚类方法. 计算机学报, Vol. 42, No. 4, pp. 820-836, 2019.

[43] 唐明董, 张婷婷, 杨亚涛, 郑子彬, 曹步清. 基于因子分解机的质量感知Web服务推荐方法. 计算机学报, 2018, 41(6): 1300-1313.

[44] 赵文玉, 周栋, 曹步清, 刘建勋. 结合文档处理与查询处理技术的Web服务搜索方法. 计算机集成制造系统 , Vol. 24, No. 7, pp. 1830-1837, 2018.

[45] 李鸿超, 刘建勋, 曹步清, 石敏. 融合多维信息的主题自适应Web API推荐方法. 软件学报, Vol. 29, No. 11, pp. 3374-3387, 2017.

指导学生的部分获奖：

 [1] 2023年湖南省优秀硕士学位论文—基于内容与用户交互关系的移动应用推荐

 [2] 2022年湖南省优秀硕士学位论文—基于内容语义和网络结构的Web服务分类方法研究

 [3] Task-role Performance Evaluation via Business Process Monitoring with BPMN Extension, CCF ICSS 2022 —最佳学生论文奖(5/6)

 [4] Service Recommendation based on Attentional Factorization Machine, IEEE SCC2019—最佳学生论文奖 (4/5)

 [5] 一种基于最佳效益与遗传算法的边缘服务器部署方法, CCF NCSC 2021—最佳论文奖(2/4)

 [6] 基于两级异质图注意力网络的Web服务QoS预测, CCF NCSC 2021—最佳论文奖(4/4)

 [7] 一种基于Gat2vec的Web服务分类方法, CCF NCSC 2019 —最佳学生论文奖(4/5)

 [8] 基于标签扩展和关联规则挖掘的Web API组合模式发现, CCF NCSC 2018 —最佳论文奖(4/4)

 [9] 基于因子分解机的质量感知Web服务推荐方法, CCF NCSC 2016 —最佳论文奖(5/5)