教授、博士生導師、副院長，“湖南省芙蓉學者獎勵計劃”青年學者、湖南省青年骨幹教師、2003网站太阳集团高層次人才“學術帶頭人”。2011年6月博士畢業于武漢大學，2014年9月至12月在香港中文大學從事訪問研究，2015年3月至2016年3月在美國阿肯色大學從事博士後工作。主要研究興趣為服務計算與邊緣計算、機器學習與推薦系統、智能化軟件與服務。在IEEE TSC、IEEE TITS、IEEE TAI、IEEE TNSM、計算機學報、軟件學報等國内外重要學術期刊以及ICWS、SCC等國際學術會議上發表論文160餘篇，其中CCF 推薦的國際學術期刊與會議論文80餘篇，中科院一區、CCF A類以及IEEE Trans系列期刊論文20餘篇，榮獲ICSS2022、NCSC2021、SCC2019等國際國内學術會議的最佳論文獎/最佳學生論文獎7次。在服務計算領域旗艦性國際學術會議ICWS上持續發表研究長文15篇。主持完成國家自然科學基金面上項目、國家重點研發計劃子課題、國家自然科學基金青年項目各1項，省部級及其他項目10餘項。獲批軟件著作權15項，申請/授權發明專利11項。主持獲得湖南省高等教育教學成果獎一等獎1項，指導學生獲得湖南省優秀碩士學位論文2篇、中國互聯網+國賽銅獎/省賽金獎2項以及湖南省程序設計競賽二等獎等省級以上獎項10餘項。現為CCF高級會員、CCF服務計算專委會常務委員、CCF協同計算專委會委員，《International Journal of Cloud Computing》雜志編委，湖南省高教學會計算機教育專委會常務理事，湖南省大學計算機教指委委員，曾任國際服務計算學會中國青年學者論壇（SSYSF）副主席，YOCSEF長沙學術秘書、學術委員。協助或組織承辦SCA2012/GCC2012、CCF NCSC2017/CBPM2017以及ChineseCSCW2021等國際學術會議/CCF學術年會3次，擔任20餘個國際國内學術會議的組織委員會主席、程序委員會委員以及多個學術期刊審稿人，榮獲CCF會員發展優秀獎/SSYSF傑出服務獎。參編計算機科學前沿叢書·十講系列—“服務計算十講”。目前指導博士生4名，碩士生11名。

聯系方式：bqcao@hnust.edu.cn; 13047225827

主持（完成）的部分科研項目：

[1] 國家自然科學基金面上項目, “機器學習增強的服務混搭開發方法研究” (61873316, 2019.1-2022.12，完成).

[2] 國家重點研發計劃子課題, “服務需求和語義建模工具集研發” (2018YFB1402800-04, 2019.1-2022.12，完成).

[3] 國家自然科學基金青年項目, “雲環境下的服務信任評估及組合優化研究” (61402168, 2015.1-2017.12，完成).

[4] 湖南省自然科學基金, “基于圖神經網絡的智能服務推薦方法研究” (2021JJ30274, 2021.1-2023.12，完成).

[5] 湖南省自然科學基金, “大數據環境下機器學習支持的服務挖掘方法研究” (2017JJ2098, 2018.1-2020.12，完成).

[6] 湖南省自然科學基金, “網絡化軟件按需服務中的高可信關鍵技術研究” (12JJB009, 2012.12-2014.12，完成).

[7] 軟件工程國家重點實驗室開放基金, “基于社會網絡的軟件服務可信評估及協同優化研究” (SKLSE2014-10-10, 2015.1-2016.12，完成).

[8] 網絡與交換技術國家重點實驗室開放基金, “基于機器學習的雲服務網絡挖掘方法研究” (SKLNST-2016-2-26, 2017.1-2018.12，完成).

發表的部分學術論文：

[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] 劉建勳, 丁領航, 康國勝, 曹步清, 肖勇. 基于特征深度融合的Web服務QoS聯合預測. 通信學報, Vol. 43, No. 7, pp. 215-226, 2022.

[40] 肖勇, 劉建勳, 胡蓉, 曹步清, 曹應成. 基于GAT2VEC的Web服務分類方法. 軟件學報, Vol. 32, No. 12, pp. 3751-3767, 2021.

[41] 曹步清, 肖巧翔, 張祥平, 劉建勳. 融合SOM 功能聚類與DeepFM質量預測的API 服務推薦方法. 計算機學報, Vol. 42, No. 6, pp. 1367-1383, 2019.

[42] 石敏, 劉建勳, 周棟, 曹步清, 文一憑. 基于多重關系主題模型的Web服務聚類方法. 計算機學報, Vol. 42, No. 4, pp. 820-836, 2019.

[43] 唐明董, 張婷婷, 楊亞濤, 鄭子彬, 曹步清. 基于因子分解機的質量感知Web服務推薦方法. 計算機學報, 2018, 41(6): 1300-1313.

[44] 趙文玉, 周棟, 曹步清, 劉建勳. 結合文檔處理與查詢處理技術的Web服務搜索方法. 計算機集成制造系統 , Vol. 24, No. 7, pp. 1830-1837, 2018.

[45] 李鴻超, 劉建勳, 曹步清, 石敏. 融合多維信息的主題自适應Web API推薦方法. 軟件學報, Vol. 29, No. 11, pp. 3374-3387, 2017.

指導學生的部分獲獎：

 [1] 2023年湖南省優秀碩士學位論文—基于内容與用戶交互關系的移動應用推薦

 [2] 2022年湖南省優秀碩士學位論文—基于内容語義和網絡結構的Web服務分類方法研究

 [3] Task-role Performance Evaluation via Business Process Monitoring with BPMN Extension, CCF ICSS 2022 —最佳學生論文獎(5/6)

 [4] Service Recommendation based on Attentional Factorization Machine, IEEE SCC2019—最佳學生論文獎 (4/5)

 [5] 一種基于最佳效益與遺傳算法的邊緣服務器部署方法, CCF NCSC 2021—最佳論文獎(2/4)

 [6] 基于兩級異質圖注意力網絡的Web服務QoS預測, CCF NCSC 2021—最佳論文獎(4/4)

 [7] 一種基于Gat2vec的Web服務分類方法, CCF NCSC 2019 —最佳學生論文獎(4/5)

 [8] 基于标簽擴展和關聯規則挖掘的Web API組合模式發現, CCF NCSC 2018 —最佳論文獎(4/4)

 [9] 基于因子分解機的質量感知Web服務推薦方法, CCF NCSC 2016 —最佳論文獎(5/5)