导师介绍
姓名 罗平 性别 男
联系方式 职称 副研究员
研究方向 数据挖掘，机器学习，大数据新型应用

个人介绍
简历:
　　罗平于2007年在中科院计算所获得博士学位。毕业后，就职于惠普研究院，任研究员、高级研究员等职位，于2014年加入中国科学院计算技术研究所智能信息处理重点实验室任副研究员。
　　罗平研究兴趣主要集中在：机器学习与数据挖掘，以及大数据下的实际新型应用。近几年，在包括SIGKDD, IJCAI, CIKM, ICDM等顶级国际会议和TKDE, TIT, TKDD等顶级国际期刊上发表三十几篇高质量论文，获得知识管理领域重要学术会议ACM CIKM“最佳学生论文”奖，并两次获得国际主流学术会议“最佳论文提名奖”。担任过2012年SIGKDD会议Poster Session主席，2013年IEEE ICDM会议Poster Session主席，和多次担任SIGKDD, WWW, CIKM, ICDM等顶级国际会议的程序委员会委员。在机器学习和数据挖掘领域取得了一定国际影响。
最新更新参见国科大教师主页：http://210.76.211.71/~luop
　　国际学术会议组织
　　Poster Session主席, ACM SIGKDD, 2012
　　Poster Session主席, IEEE ICDM, 2013
　　国际学术会议程序委员
　　SIGKDD, 2013; SIGKDD, 2012; SIGKDD, 2011; SIGKDD, 2010
　　WWW, 2013; SDM, 2014; SDM, 2013; ICDM, 2013
　　CIKM, 2011; ECML, 2011; WAIM, 2014; WAIM, 2013
　　国际刊物审稿人
　　IEEE Transactions on Knowledge and Data Engineering
　　ACM Transactions on Intelligent Systems and Technology
　　Data Mining and Knowledge Discovery Journal
　　Knowledge and Information Systems
　　Information Sciences
　　Statistical Analysis and Data Mining Journal
　　China Science Bulletin
　　曾指导过的学生情况：
　　汤林鹏（来自上海交通大学），现为Princeton博士研究生
　　尹培风（来自Penn State），现为Penn State博士研究生
　　姜啸（来自上海交通大学），现在Facebook USA工作
　　马旭东（来自中科院计算所），现在Google USA工作
　　肖涵（来自北京邮电大学），现为Technische Universitat Munchen (慕尼黑理工)博士研究生
　　庄福振（来自科学院计算所），现为计算所副研究员
　　林芬（来自科学院计算所），现在腾讯工作
　　研究工作报道：
　　借三国，看IT——透过早期投票占卜“火帖”
　　手机APP上演的《甄嬛传》
　　基于占有度的模式推荐
　　欢迎有志于研究的学生报考我的研究生（硕士、博士）！

　　

研究方向:
数据挖掘，机器学习，大数据新型应用

社会任职:
国际学术会议组织:
　　Poster Session主席, ACM SIGKDD, 2012
　　Poster Session主席, IEEE ICDM, 2013
　　
国际学术会议程序委员:
　　SIGKDD, 2013; SIGKDD, 2012; SIGKDD, 2011; SIGKDD, 2010
　　WWW, 2013; SDM, 2014; SDM, 2013; ICDM, 2013
　　CIKM, 2011; ECML, 2011; WAIM, 2014; WAIM, 2013
　　
国际刊物审稿人:
　　IEEE Transactions on Knowledge and Data Engineering
　　ACM Transactions on Intelligent Systems and Technology
　　Data Mining and Knowledge Discovery Journal
　　Knowledge and Information Systems
　　Information Sciences
　　Statistical Analysis and Data Mining Journal
　　China Science Bulletin

　

获奖及荣誉:
　　1.中国计算机学会优秀博士论文奖, 2009
　　2.ACM CIKM 最佳学生论文奖（论文“Incorporating Occupancy into Frequent Pattern Mining for High Quality Pattern Recommendation”），2012
　　3.ACM CIKM 最佳论文提名奖（论文“Collaborative Dual-PLSA: Mining Distinction and Commonalityacross Multiple Domains for Classification”），2010
　　4.SIAM on Data Mining 最佳论文提名奖（论文“Exploiting Associations between Word Clusters and Document Classes for Cross-domain Text Categorization”），2010
　　5.中国科学院优秀毕业生，2007
　　6.中国科学院计算技术研究所所长特别奖学金，2007



代表论著:
　　国际会议
　　1.[KDD] Peifeng Yin, Ping Luo, Wang-Chien Lee, Min Wang. “Silence is also evidence: Interpreting dwell time for recommendation from Psychological Perspective". In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2013.
　　2.[KDD] Wei Shen, JianyongWang, Ping Luo, MinWang. “Linking Named Entities in Tweets with Knowledge Base via User Interest Modeling". In Proceedings of the 19th ACM SIGKDD International Conferenceon Knowledge Discovery and Data Mining (KDD), 2013.
　　3.[KDD] Lei Zhang, Linpeng Tang, Ping Luo, Enhong Chen, Limei Jiao, Min Wang, Guiquan Liu. “Harnessing the Wisdom of the Crowds for Accurate Web Page Clipping". In Proceedings of the 18th ACMSIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012.
　　4.[KDD] Wei Shen, Jianyong Wang, Ping Luo, Min Wang. “LIEGE: Link Entities in Web Lists with Knowledge Base". In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012.
　　5.[KDD] Xiao Jiang, Chengkai Li, Ping Luo, Min Wang, Yong Yu. “Prominent Streak Discovery in SequenceData". In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2011.
　　6.[KDD] Ping Luo, Fen Lin, Yuhong Xiong, Yong Zhao, Zhongzhi Shi. “Towards Combining Web Classification and Web Information Extraction: a Case Study". In Proceedings of the ACM 15th International Conference on Knowledge Discovery and Data Mining (KDD), 2009.
　　7.[KDD] Ping Luo, Hui Xiong, Kevin Lu¨, Zhongzhi Shi. “Distributed Classification in Peer-to-Peer Networks". In Proceedings of the ACM 13th International Conference on Knowledge Discovery and Data Mining (KDD), 2007.
　　8.[IJCAI] Fuzhen Zhuang, Ping Luo, Peifeng Yin, Qing He, Zhongzhi Shi. “Concept Learning for Cross-domain Text Classification: a General Probabilistic Framework”. In Proceedings of the 23nd International Joint Conference on Artificial Intelligence (IJCAI), 2013.
　　9.[IJCAI] Xudong Ma, Ping Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi, Zhiyong Shen. “Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding". In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), 2011.
　　10.[CVPR] Ke Gao, Yongdong Zhang, Ping Luo, Wei Zhang, Junhai Xia, Shouxun Lin. “Visual Stem Mapping and Geometric Tense Coding for Augmented Visual Vocabulary". In Proceedings of the 25th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
　　11.[CIKM] Wei Shen, Jianyong Wang, Ping Luo, Min Wang. “A Graph-Based Approach for Ontology Population with Named Entities". In Proceedings of the 21th ACM Conference on Information and Knowledge Management (CIKM), 2012.
　　12.[CIKM] Linpeng Tang, Lei Zhang, Ping Luo, Min Wang. “Incorporating Occupancy into Frequent PatternMining for High Quality Pattern Recommendation". In Proceedings of the 21th ACM Conference on Information and Knowledge Management (CIKM), 2012. (最佳学生论文)
　　13.[CIKM] Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi, Hui Xiong. “Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Classification". In Proceedings of the 19th ACM Conference on Information and Knowledge Management (CIKM), 2010. (最佳论文提名)
　　14.[CIKM] Ping Luo, Fuzhen Zhuang, Hui Xiong, Yuhong Xiong, Qing He. “Transfer Learning from Multiple Source Domains via Consensus Regularization". In Proceedings of the ACM 17th Conference on Information and Knowledge Management (CIKM), 2008.
　　15.[ICDM] Lili Jiang, Ping Luo, Jianyong Wang, Yuhong Xiong, Bingduan Lin, Min Wang, Ning An. “GRIAS: an Entity-Relation Graph based Framework for Discovering Entity Aliases". In Proceedings of the 12th IEEE International Conference on Data Mining (ICDM), 2013.
　　16.[ICDM] Guangxiang Zeng, Ping Luo, Enhong Chen, Min Wang. “From Social User Activities to People Affiliation". In Proceedings of the 12th IEEE International Conference on Data Mining (ICDM), 2013.
　　17.[ICDM] Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi. “D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification". In Proceedings of the 9th IEEE International Conference on Data Mining (ICDM), 2010.
　　18.[ICDM] Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen. “Topic Modeling Ensembles". In Proceedings of the 9th IEEE International Conference on Data Mining (ICDM), 2010.
　　19.[ICDM] Zhiyong Shen, Ping Luo, Yuhong Xiong, Jun Sun, Yidong Shen. “Topic Modeling for Sequences of Temporal Activities". In Proceedings of the 8th IEEE International Conference on Data Mining (ICDM),2009.
　　20.[WWW] Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He, Zhongzhi Shi. “Discovering and Learning Sensational Episodes of News Events”. WWW 2014.
　　21.[WWW] Wei Shen, Jianyong Wang, Ping Luo, Min Wang. “LINDEN: Linking Named Entities with Knowledge Base via Semantic Knowledge". In Proceedings of the 21st World Wide Web Conference (WWW), 2012.
　　22.[SDM] Fuzhen Zhuang, Ping Luo, Hui Xiong, Qing He, Yuhong Xiong, Zhongzhi Shi. “Exploiting Associations between Word Clusters and Document Classes for Cross-domain Text Categorization". In Proceedings of the 10th SIAM International Conference on Data Mining (SDM), 2010. (最佳论文提名)
　　23.[ECML] Wenchao Yu, Ping Luo, Guangxiang Zeng, Fuzhen Zhuang, Qing He, Zhongzhi Shi. “Embedding with Autoencoder Regularization". ECML/PKDD 2013.
　　24.[WSDM] Peifeng Yin, Ping Luo, Wang-Chien Lee, Min Wang. “App recommendation: a contest between satisfaction and temptation". WSDM 2013.
　　25.[WSDM] Fuzhen Zhuang, Ping Luo, Changyin Du, Qing He, Zhongzhi Shi. "Triplex transfer learning: exploiting both shared and distinct concepts for text classification". In WSDM, 2013.
　　26.[WSDM] Peifeng Yin, Ping Luo, Min Wang, Wang-Chien Lee. "A straw shows which way the wind blows: ranking potentially popular items from early votes". In WSDM, 2012.

　　国际期刊
　　1.[TKDE] Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi, Hui Xiong. Mining Distinction and Commonality across Multiple Domains Using Generative Model for Text Classification. IEEE Transactions on Knowledge and Data Engineering 24(11): 2025-2039, 2012.
　　2.[TKDE] Fuzhen Zhuang, Ping Luo, Hui Xiong, Yuhong Xiong, Qing He, Zhongzhi Shi. “Cross-DomainLearning from Multiple Sources: A Consensus Regularization Perspective". IEEE Transactions on Knowledge and Data Engineering 22(12): 1664-1678, 2010.
　　3.[TKDE] Ping Luo, Hui Xiong, Guoxing Zhan, Junjie Wu, Zhongzhi Shi. “Information-Theoretic DistanceMeasures for Clustering Validation: Generalization and Normalization". IEEE Transactions on Knowledge and Data Engineering 21(9): 1249-1262, 2009.
　　4.[TIT] Ping Luo, Guoxing Zhan, Qing He, Zhongzhi Shi, Kevin Lu¨. “On Defining Partition Entropy by Inequalities". IEEE Transactions on Information Theory 53(9): 3233-3239, 2007.
　　5.[JPDC] Ping Luo, Kevin Lu¨, Zhongzhi Shi. “A Revisit of Greedy Heuristic for Mapping a Class of Independent Task onto Heterogeneous Computing Systems". Journal of Distributed and Parallel Computing 67:695-714, 2007.
　　6.[TKDD] Gensheng Zhang, Chengkai Li, Ping Luo, Xiao Jiang, Min Wang. “Discovering General ProminentStreaks in Sequence Data". ACM Transactions on Knowledge Discovery from Data, 2013. (accepted)
　　7.[Information Sciences]Xiang Ao, Ping Luo, Xudong Ma, Fuzhen Zhuang, Qing He, Zhongzhi Shi, Zhiyong Shen. “Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding". Information Sciences, 2014.
　　8.[Information Sciences] Ning An, Lili Jiang, Jianyong Wang, Ping Luo, Min Wang, Bing Nan Li. “Toward detection of aliases without string similarity. Information Sciences”. Information Sciences, 2014.
　　9.[DKE] Xu Pu, Jianyong Wang, Zhenhua Song, Ping Luo, Min Wang. “Efficient incremental update and querying in AWETO RDF storage system”. Data Knowledge Engineering, 2014.
　　10.[TSMC] Fuzhen Zhuang , Ping Luo , Changying Du , Qing He , Zhongzhi Shi. “Triplex transfer learning: exploiting both shared and distinct concepts for text classification”. IEEE Transaction on SMC-Part B, 2014.



承担科研项目情况:

学科类别:

所属部门:
智能信息处理重点实验室
专家类别:
副高
****入选时间:

百人入选时间:

其他备注:
博导计算机软件与理论
其他备注2:

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