杨彦武于2006年从法国ENSAM大学获计算机科学博士学位，长期致力于互联网环境下的搜索推荐与广告策略方面的研究工作，从学科交叉性(计算机科学、运筹学、信息系统和经济计算)的角度探讨互联网条件下搜索推荐和广告策略优化等关键技术。已完成学术著作1部，发表学术论文40余篇，其中国际期刊论文13篇。2007年起主持科技部863专题项目1项、国家自然科学基金面上项目2项和北京市自然科学基金面上项目1项，作为技术骨干参与科技部863重大项目1项、国家自然科学基金电子商务重大研究计划子项目1项和中国科学院创新项目2项。积极参与国际交流，担任多个主流学术期刊与会议的审稿工作，以及多个主流学术组织的会员和专业委员会委员。现任国际期刊IEEE Intelligent Systems（IS）的客座编辑（Guest Editor）和The Journal of Finance and Data Science (JFDS)的副主编（Associate Editor）。

Call for Papers

IEEE Intelligent Systems (IS) Special Issue on Computational Advertising

Submission Deadline: May 1, 2016

讲授课程

　　市场研究 (Marketing Research)、

　　营销工程 (Marketing Engineering)

社会网络分析 (Social Network Analysis)

搜索引擎营销 (Search Engine Marketing)

营销管理 (Marketing Management)

学术论文(Refereed)

　　Yang, Y., D. Zeng, Y. Yang, (2015) Optimal Budget Allocation across Search Advertising Markets, INFORMS Journal on Computing, 27(2), 285-300.

     Ortiz-Cordova, A., Yang, Y., and Jansen, B. J. (2015) External to Internal search: Associating Searching on Search Engines with Searching on Sites. Information Processing & Management. 51(5), 718–736.

　　Yang, Y., R. Qin, B.J. Jansen, J. Zhang, D. Zeng, (2014) Budget Planning for Coupled Campaigns in Sponsored Search Auctions, International Journal of Electronic Commerce, Vol. 18, No. 3, pp. 39–66, Spring 2014.

　　Zhang, J., Y. Yang*, X. Li, R. Qin, D. Zeng, (2014) Dynamic Dual Adjustment of Daily Budgets and Bids in Search Auctions, Decision Support Systems, 57: 105-114, January 2014. (Corresponding author)

　　Qi, J., Z. Chao, Y. Yang, (2014) Recommendations based on Social Relationships in Mobile Services, Systems Research and Behavioral Science, Vol. 31, No. 3, pp. 424–436, May/June 2014.

　　Yang, Y., J. Zhang, R. Qin, J. Li, B. Liu, Z. Liu (2013). Budget Optimization Strategies in Uncertain Environments of Search Auctions: A Preliminary Investigation. IEEE Transactions on Services Computing, 6 (2): 168-176, April-June 2013.

　　Yanwu Yang, Xin Li, An Artificial Society-based Simulation Framework for Sponsored Search Auctions, In Proceedings of the 23th Workshop on Information Technologies and Systems (WITS’13), Milan, Italy, 14-15th Dec, 2013.

　　Yanwu Yang, Yinghui Yang, Xunhua Guo, Daniel Zeng, Keyword Optimization in Sponsored Search Advertising: A Multi-Level Computational Framework. In Proceedings of the 23th Workshop on Information Technologies and Systems (WITS’13), Milan, Italy. 14-15th Dec, 2013.

　　Yang, Y., J. Zhang, R. Qin, J. Li, F. Wang, W. Qi (2012). A Budget optimization framework for search advertisements across markets, IEEE Transactions on Systems, Man, and Cybernetics. Part A: Systems and Humans, 42(5): 1141-1151 (2012).

　　Yang, Y., Personalized search strategy for spatial information on the Web, IEEE Intelligent Systems, 27(1): 12-20 (2012).

　　Xiarong Li, Daniel D. Zeng, Yong Liu, Yanwu Yang, Click Fraud and the Adverse Effects of Competition, IEEE Intelligent Systems, vol. 26, no. 6, pp. 31-39, Nov./Dec. 2011.

　　Yang, Y., C. Claramunt, M.-A. Aufaure, User-centric Similarity and Proximity Measures for Spatial Personalization, International Journal of Data Warehousing and Mining, 6(2):59-78, 2010.

　　Xia,F., Yang, Y., F. Li, J. Wang, A Closed-Form Reduction of Multi-class Cost-Sensitive Learning to Weighted Multi-class Learning, Pattern Recognition, Vol.42, No.7, 2009:1572-1581.

　　Xia,F., W. Zhang, F. Li and Y. Yang, Ranking with Decision Tree, Knowledge and Information Systems, vol.17, no. 3, pp.381-395, 2008..

　　Xia,F., L. Zhou, Y. Yangand W. Zhang, Ordinal Regression as Multiclass Classification. The Internal Journal of Intelligent Control System, Vol. 12 (3), Sep 2007, 230-238.

　　Yang, Y. and Claramunt, C., 2003, A process-based multi-representation of gradual changes, Journal of Geographical Decision Analysis, 7 (1), 1-13.

　　杨彦武等，2013. 搜索竞价中关键字最优化策略. 信息系统学报，12: 9-23.

　　杨彦武等. 跨搜索引擎关键字竞价广告预算分配策略. 科技导报, 29(04):18-24, 2011.

Future Students

　　For academic careers

　　(1)Basic math and computing skill; (2) Well-motivated research enthusiasm; (3) Big interests to pursue novel issues between business and information technologies. Pursuing a Ph.D is a major life undertaking.

　　For industrial careers

　　(1)Good experience in business or IT; (2)Well-motivated research enthusiasm; (3)Big interests to explore opportunities between business and information technologies.