基本信息

刘莹 女 教授 计算机科学与技术学院
电子邮件:yingliu@gucas.ac.cn
通信地址:中关村东路80号青年公寓6号楼215
邮政编码:100190

部门/实验室:计算机与控制学院

研究领域

数据挖掘,并行计算,大数据分析

科研项目

  • 中国科学院大学 

主持中国科学院遥感所开放课题《遥感图像舰船检测识别算法研究》,2017-2018

主持华为公司横向课题《GPU云DCN超低时延性能分析》,2017-2018

主持广东省科技计划项目应用型科技研发专项子项目《城市公共交通大数据开放平台研发与产业化》,2016-2019

主持自然科学基金面上项目《基于多源异构大数据的互联网信贷信用评分关键技术》,2017-2020

主持中国科学院大学院所合作项目《基于多源异构大数据的互联网信贷系用评分研究》,2016-2018

主持横向课题《现场测试管理系统软件》,2016

主持横向课题《嵌入式图像处理模块》,2015

主持总装备部某项目《基于麒麟OS的高速信号记录与分析软件系统研制》,2014~2015

主持横向课题《宽带电磁环境监测系统频谱监测软件》,2014~2019

主持重点学科建设项目《大规模开放网络课程(MOOC):数据挖掘》,2014

主持中国互联网信息中心实验室开放课题项目《域名解析日志数据及用户注册数据挖掘技术研究》,2013 ~ 2014
主持自然科学基金《面向海量数据的基于效用的个性化学术资源推荐系统关键技术研究》(61202321),2013~2015
主持中国科学院大学“精品数字课程”项目,2012
主持中国互联网信息中心实验室开放课题项目《域名解析数据挖掘技术研究》,2012 ~ 2013
主持美国安捷伦公司全球大学研究基金项目《基于云的科学模拟计算平台研究》,2012 ~ 2013
主持企业横向课题《高性能交通稽查计算系统平台》,2012
主持美国安捷伦公司横向课题《跨平台的图形处理器加速数据图形显示技术》,2010~2011
主持国家自然科学基金委创新群体项目子课题《海量数据的挖掘技术的研究》,2007 ~ 2012
主持国家自然科学基金委重点项目子课题《可信软件过程的基本属性和度量模型》,2008 ~ 2010
主持美国英伟达公司横向课题《基于CUDA的并行数据挖掘》,2009
主持教育部留学归国人员科研启动基金《基于传感器网络的交通数据流挖掘》,2009 ~ 2010
主持中国科学院研究生院院长基金《效用挖掘的理论研究及应用》, 2009 ~ 2010
主要负责中国人民银行横向课题《个人信用评分系统》,2006~2007 


  • Ultra-Scale Computing Laboratory, Northwestern University

参加美国国家科学基金(NSF)项目,High-Performance Techniques, Designs and Implementation of Software Infrastructure for Change Detection and Mining (IIS-0536994)
参加美国能源部项目,Scientific Data Management Integrated Software Infrastructure Center
参加Intel公司项目,Characterizing Scalable Data Mining Kernels/Primitives on SMP’s

招生专业
081202-计算机软件与理论
081203-计算机应用技术
招生方向
数据挖掘、并行计算

招生专业
081202-计算机软件与理论
081203-计算机应用技术
学术兼职

任2016大数据智能论坛共同主席

任中国计算机学会高性能计算专业委员会委员,2014 – 今

任Data Science Journal编委
任Annals of Data Science客座主编
任2015-2019全国科学数据大会程序委员会委员
任2014-2019 International Conference on Information Technology and Quantitative Management高性能数据分析分会主席
任2014全国科学数据大会程序委员会共同主席
任2013 International Conference on Information Technology and Quantitative Management程序委员会委员
Journal of Parallel Computing, 审稿人
Journal of World Wide Web, 审稿人
《软件学报》,审稿人
IEEE  Transaction on Parallel and Distributed System, 审稿人
Decision Sciences,审稿人
《科研信息化技术与应用》,审稿人
《计算机学报》,审稿人
IEEE/WIC/ACM International Conference for Web Intelligence, 2012, 2013, 2014,审稿人
Journal of Supercomputing, 审稿人
任全国高性能计算年会 (HPCChina) 程序委员会委员,2012、2013、2014、2015
任3rd Informational Center for Computational Science Workshop程序委员会委员, 2012
担任NVIDIA2009、2010、2011、2012年全国CUDA 校园程序设计大赛评委
任第二届、第三届国际网络社会研讨会(SWS2010, SWS2011)程序委员会委员
2nd International Conference on Computational and Systems Biology程序委员会委员, 2010
任第七届国际计算科学大会(ICCS2007)地方组委成员
任第七届国际计算科学大会(ICCS2007)高性能数据挖掘研讨会主席
任第七届国际数据挖掘大会(ICDM2007)高性能数据挖掘研讨会主席
任第278次香山会议“数据技术与知识经济若干科学前沿问题“组委成员
7th International Conference on Computational Science (ICCS), 2007, 审稿人
SIAM International Conference on Data Mining (SDM), 2005, 审稿人
International Symposium on Parallel and Distributed Processing and Applications (ISPA), 2004, 审稿人
IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2008,审稿人
IEEE Youth Conference on Information, Computing and Telecommunications, 2009, 2010审稿人
International Journal of Information Technology and Decision Making,审稿人
IEEE Transactions on Systems, Man, and Cybernetics (TSMC), 审稿人
IEEE Transactions on Knowledge and Data Engineering (TKDE), 审稿人
《管理科学学报》,审稿人

教育背景

   
学位
北京大学-- 学士,1999
美国Northwestern University -- 硕士,2001
美国Northwestern University -- 博士 ,2005

工作经历

中国科学院大学计算机科学与技术学院,教授 2015.12 ~ 今
中国科学院大学计算机科学与技术学院,副教授 2007. 6 ~ 2015.11 
美国内布拉斯加大学奥马哈分校,访问学者 2009.7 ~ 2009.9
中国科学院研究生院信息科学与工程学院, 讲师 2006.1 ~ 2007.5
美国Northwestern University,研究助理 2005.6 ~ 2005.11

教授课程

高性能计算系统II(B)、 数据挖掘算法研究讨论班、 数据挖掘、 数据挖掘算法研究、 高性能计算系统 II(B)、 数据挖掘引论、 高性能计算的新发展——基于图形处理器的并行计算及CUDA编程、 数据挖掘高级技术
研究生课程

  • 中国科学院大学计算机科学与技术学院
       
    《高性能计算的新发展——基于图形处理器的并行计算及CUDA编程》 2009.2 ~ 今
       《数据挖掘引论》 2006.9 ~ 今
       《数据挖掘高级技术》 2007.2 ~ 2010.6
       《数据挖掘算法讨论班》2009.9 ~ 今
  • 中国科学院大学国际学院
       《数据挖掘》 2013.9 ~ 今
  • 中国科学院研究生院计算与通信工程学院
       《数据挖掘》 2007.3 ~ 2007.5

 

培训课程

  • 北京理工大学,《高级CUDA编程及应用》,2018.09

  • 航天部九院704所,《异构并行计算与大数据分析》,2017.10

  • 广东省经济和信息化委大数据应用培训班,《大数据分析与挖掘》,2016.07-2016.08

  • 交通部规划研究院,《大数据》,2016.05

  • 中国科学院遥感与对地观测中心博士班课程 ,《大数据分析》,2015.11            

  • 中国科学院发展中国家科学大数据国际培训班,《大数据挖掘》,2015.5
  • 中国人民大学新闻学院暑期工作坊,《大数据挖掘》,2014.7
  • 大连理工大学,《基于图形处理器的并行计算及CUDA编程》,2014-2015
  • 中国科学院大学中丹学院,《数据挖掘及其应用》,2013-2015
  • 中国科学院大学管理学院MBA课程,《数据挖掘及其应用》,2011-2015
  • 中国科学院国家天文台,《基于图形处理器的并行计算及CUDA编程》                     2013.10
  • 中国科学院软件研究所,《数据挖掘》,2010. 8
  • 中国科学院,《基于图形处理器的并行计算及CUDA编程》,2009 - 2016
  • 安捷伦科技有限公司(中国),《基于图形处理器的并行计算及CUDA编程》,2009. 6

专利与奖励

   
奖励信息

获2017年中国科学院“朱李月华”优秀教师奖

获2017 International Conference on Information Technology and Quantitative Management最佳论文奖

获2015 International Conference on Information Technology and Quantitative Management最佳论文奖

获2015全国科学数据大会最佳展示奖

获美国英伟达公司2014年度最佳教学中心称号(中国)
获美国英伟达公司2013全球研究中心
获美国英伟达公司2012全球教学中心
获2011年北京市科学技术奖二等奖,编号2011计-2-002,项目《最优化信用评分体系与应用》,本单位排名第四
获2010年北京市科学技术奖三等奖,编号2010基-3-004,项目《多目标规划数据挖掘理论、方法及在重要行业中的应用》,本单位排名第四
获2012中国科学院大学“精品数字课程”项目
获中国科学院研究生院2011-2012学年度优秀课程
获中国科学院研究生院2010-2011学年度优秀课程
获中国科学院研究生院2009-2010学年度优秀课程
获中国科学院研究生院2007-2008学年度优秀课程
获2010-2011学年中国科学院研究生院“我最喜爱的研究生课程主讲老师”称号

专利信息

中科航天设备地面验证系统数据库管理系统,软件著作权登记号:2015SR067986
基于云的并行ESL仿真和通信仿真系统中间件,软件著作权登记号:2015SR069425
基于效用的个性化学术资源推荐系统,软件著作权登记号:2015SR181976

航天测控中频检前信号分析软件,软件著作权登记号:2016SR270133

基于麒麟操作系统中频检前记录系统控制软件,软件著作权登记号:2016SR270126

深空测控干涉测量系统基带转换与记录设备软件,软件著作权登记号:2016SR242771



发表论文

   
专著

[1] 李国庆,刘莹,庞禄申,《地球科学中的大数据分析与挖掘算法手册》,人民邮电出版社,2018.

[2] 赵地,刘莹等,《强化学习》,机械工业出版社,2018 

[3] 文跃然,刘莹等,《人力资源管理学习精要——基于人工智能的方法》,复旦大学出版社,ISBN:9787309136944/F.2463,2018。

[4] 刘莹,《大数据挖掘》,大数据时代的科研活动,科学出版社,ISBN:9787030401830,2014。

[5] Xiaojun Li, Yang Gao, Xinyu Ma, Ying Liu, “Performance Evaluation of Fast Fourier Transform Application on Heterogeneous Platforms”, GPU Solutions to Multi-scale Problems in Science and Engineering. David A. Yuen, Long Wang, et al. ed., Springer, 2013. ISBN-10: 3642164048.

[6] Jianwei Li, Ying Liu, Wei-keng Liao, Alok Choudhary, “Parallel Data Mining Algorithms for Association Rules and Clustering”, Handbook of Parallel Computing: Models, Algorithms and Applications. Sanguthevar Rajasekaran and John Reif, ed., CRC Press, 2007.

期刊论文

[1] Ying Liu, Hongyuan Cui, Renliang Zhao, “Fast Acquisition of Spread Spectrum Signals using Multiple GPUs”, IEEE Transactions on Aerospace and Electronic Systems, DOI: 10.1109/TAES.2019.2902695

[2] Jiaxu Leng, Ying Liu, Real-Time RGB-D Visual Tracking With Scale Estimation and Occlusion Handling, IEEE Access 2018,DOI: 10.1109/ACCESS.2018.2831443.

[3] Jiaxu Leng, Ying Liu, “An enhanced SSD with feature fusion and visual reasoning for object detection”, Neural Computing and Applications, 2018, DOI: 10.1007/s00521-018-3486-1.

[4] Ying Liu, Guoyu Ou, “Real-Time Vehicular Traffic Violation Detection in Traffic Monitoring Stream”, Journal of Intelligent Transportation Systems,  Vol. 22, (1) 2018.

[5] Ying Liu, Haixin Zheng, Renliang Zhao, Liheng Jian, “Design and Evaluation of Multi-GPU enabled Multiple Symbol Detection Algorithm”, Journal of Supercomputing, Vol. 72(6), 2016.6, pp. 2111-2131, DOI 10.1007/s11227-015-1475-z.

[6] Zhongya Wang, Ying Liu, Jiajun Yang, Zheng Zheng, Kaichao Wu, “A Personalization-Oriented Academic Literature Recommendation Method”, Data Science Journal, 2015, DOI: http://doi.org/10.5334/dsj-2015-017.

[7] Hongyuan Cui, Jiajun Yang, Ying Liu, Zheng Zheng, Kaichao Wu, “Data Mining-based DNS Log Analysis”, Annals of Data Science, DOI: 10.1007/s40745-014-0023-7.

[8] Zhongya Wang, Ying Liu, Steve Chiu, “An Efficient Parallel Collaborative Filtering Algorithm on Multi-GPU Platform”, Journal of Supercomputing, Vol. 72(6), 2016.6, pp 2080-2094, DOI:10.1007/s11227-014-1333-4. 
[9] Yuwei Wang, Yuanchun Zhou, Ying Liu, “A Grid-Based Clustering Algorithm for Wild Bird Distribution”, Frontiers of Computer Science, Vol. 7(4), 2013, pp. 475-485. DOI:10.1007/s11704-013-2223-2.
[10] Liheng Jian, Ying Liu, Weidong Yi, “CU-Simulator: A Parallel Scalable Simulation Platform for Radio Channel in Wireless Sensor Networks”, Ad Hoc & Sensor Wireless Networks, Vol.24, pp. 109-134.
[11] Liheng Jian, Cheng Wang, Ying Liu, Shenshen Liang, Weidong Yi, Yong Shi, "Parallel Data Mining on Graphics Processing Unit with Compute Unified Device Architecture (CUDA)", Journal of Supercomputing, Vol. 64(3), 2013, pp. 942-967.
[12] Ying Liu, Lingling Zhang, Yuehua Zhang, Yong Shi, " Bug Detection in Source Code in Process Monitoring", Journal of Computational Information System, Vol. 8(2), 2012, pp. 591-601.
[13] Ying Liu, Jianwei Li, Wei-keng Liao, Alok Choudhary, Yong Shi, “High Utility Itemsets Mining”, International Journal of Information Technology & Decision Making (IJITDM), Volume No.09, Issue No. 6, November 2010, pp. 905-934.
[14] Yuejin Zhang, Lingling Zhang, Ying Liu, Yong Shi, "Mining Intelligent Knowledge from a Two-phase Association Rules Mining", International Journal of Data Mining, Modeling and Management, Vol. 2, No. 4, 2010, pp. 403-418.
[15] Lian Duan, Lida Xu, Ying Liu and Jun Lee, “Cluster-based Outlier Detection”, Annals of Operations Research, Vol. 168, No.  1, April 2009, pp. 151-168.
[16] Guangli Nie, Lingling Zhang, Ying Liu, Xiuyu Zheng, Yong Shi, "Decision analysis of data  mining project based on Bayesian risk", Journal of Expert Systems with Applications, Vol. 36, Issue 3, Part 1, April 2009, pp. 4589–4594.
[17] Cheng Wang, Ying Liu, Liheng Jian, Peng Zhang, "An Efficient Approach for Mining Web Content Sensitivity", International Journal of Knowledge and Web Intelligence, Vol. 1, Nos. 1/2, 2009, pp. 95-109.
[18] 陈源,王元钦,刘莹,《基于GPU加速的扩频信号捕获方法》,中国科学院研究生院学报, 2012年02期,pp. 240-245。
[19] 陈源,王元钦,刘莹,门陶,《基于通用计算机平台的航天测控系统研究》,测控技术, 2011年04期,pp. 8-12。   
[20] 陈源,王元钦,刘莹,《基于CORBA的扩展型事件服务模型设计 》,计算机应用, S1期, pp 138-140+143, 2011。    
[21] 刘莹,菅立恒, 梁莘燊, 李小君,高洋,王琤,《基于CUDA架构的GPU的并行数据挖掘技术研究》,科研信息化技术与应用,2010年第4期,pp. 37-52。

会议论文

[1] Tianlin Zhang, Ying liu, Pei Quan, "Domain Specific Automatic Chinese Multiple-type Question Generation", IEEE International Conference on Bioinformatics and Biomedicine, December 2018, Spain.

[2] Jiaxu Leng, Ying Liu, Tianlin Zhang, Pei Quan, Zhenyu Cui, "Context-Aware U-Net for Biomedical Image Segmentation", IEEE International Conference on Bioinformatics and Biomedicine, December 2018, Spain.

[3] Jiaxu Leng, Ying Liu, Tianlin Zhang, Pei Quan, "Context Learning Network for Object Detection", IEEE International Conference on Data Mining, November 2018, Singapore.

[4] Pei Quan, Yong Shi, Lingfeng Niu, Ying Liu, Tianlin Zhang, "Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal", International Academy of Information Technology and Quantitative Management, December 2018, USA.

[5] Ying Liu, Linzhi Wu, “High Performance Geological Disaster Recognition using Deep Learning”, International Academy of Information Technology and Quantitative Management, December 2018, USA.

[6] Pei Quan, Ying Liu, Tianlin Zhang, “A Novel Data Mining Approach Towards Human Resource Performance Appraisal”, ICCS, May 2018, China.

[7] Ying Liu, Tianlin Zhang, Pei Quan, “A Novel Parsing-Based Automatic Domain Terminology Extraction Method”, ICCS, May 2018, China.

[8] Ying Liu, Jinyi Liu, “Recognition and Classification of Rotorcraft by Micro-Doppler Signatures Using Deep Learning”, ICCS, May 2018, China.

[9] Ying Liu, Xiang Chao, “Hybrid Learning Network: A Novel Architecture for Fast Learning”, International Conference on Information Technology and Quantitative Management, December 2017, India.

[10] Yan, Tao Wu, Ying Liu, Yang Gao, ”An Efficient Sparse-Dense Matrix Multiplication on a Multicore System”, 17th IEEE International Conference on Communication Technology (ICCT 2017), October 2017, China. (EI)

[11] Ying Liu, Jiajun Yang, “A Novel Learning-to-Rank Based Hybrid Method for Book Recommendation”, IEEE/WIC/ACM International Conference on Web Intelligence, September 2017, Leipzig, Germany.

[12] Ying Liu, Hongyuan Cui, Guoqing Li, “A Novel Method for Ship Detection and Classification on Remote Sensing Images”, the 26th International Conference on Artificial Neural Networks, September 2017, Italy. 

[13] Ying Liu, Hongyuan Cui, Zheng Kuang, Guoqing Li, Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning, 4th Annual International Conference on Information Technology and Applications, May 2017, China.

[14] Ying Liu, Linzhi Wu, “Disaster Recognition on Optical Remote Sensing Images Using Deep Learning”, International Conference on Information Technology and Quantitative Management, August 2016, Korea.

[15] Hongyuan Cui, Ying Liu, Cheng Wang, “A Novel Self-adaptive Density-based Clustering Algorithm for Radar Signal Sorting”, IET International Radar Conference, September 2015, Hangzhou, China.

[16] Ying Liu, Pengshan Ma, Hongyuan Cui, “Design and Development of FPGA-based High Performance Radar Data Stream Mining System”, International Conference on Information Technology and Quantitative Management, July 2015, Brazil.
[17] Ying Liu, Hongyuan Cui, “Antenna Array Signal Direction of Arrival Estimation on Digital Signal Processor (DSP)”, International Conference on Information Technology and Quantitative Management, July 2015, Brazil.
[18] Ying Liu, Jiayun Yang, “Improving Ranking-based Recommendation by Social Information and Negative Similarity”, International Conference on Information Technology and Quantitative Management, July 2015, Brazil.
[19] Zhongya Wang, Ying Liu, Pengshan Ma, “A CUDA-enabled Parallel Implementation of Collaborative Filtering”, 3rd International Conference on Data Science, Beijing, May 2014.
[20] Renliang Zhao, Haixin Zheng, Ying Liu, Liheng Jian, Xianglong Gu, Bingyin Han, Zhongya Wang, “CUDA-enabled Multiple Symbol Detection for PCM/FM Demodulation”, IEEE International Conference on Cloud and Service Computing, November 2013, Beijing, China.
[21] Guoyu Ou, Ying Liu, Xinyu Ma, Cheng Wang, “DM-Midware: A Middleware to Enable High Performance Data Mining in Heterogeneous Cloud”, Workshop in conjunction with IEEE/WIC/ACM International Conference on Web Intelligence, November 2013,  Atlanta, USA.
[22] Weizhang Ruan, Ying Liu, Renliang Zhao, “Pattern Discovery in DNS Query Traffic”, International Conference on Information Technology and Quantitative Management, May 2013, China.
[23] Guoyu Ou, Yang Gao, Ying Liu, “Real-Time Vehicular Traffic Violation Detection in Traffic Monitoring Stream”, Workshop in conjunction with IEEE/WIC/ACM International Conference on Web Intelligence, December 2012, Macau.
[24] Liheng Jian, Weidong Yi, Ying Liu, “Fast On-Chip Quad-trees on GPU”, IET International Conference on Information Science and Control Engineering, December 2012, Shenzhen, China. 
[25] Yang Gao, Ying Liu, Cheng Wang, Xiaojun Li, Guoyu Ou, Yong Shi, “Design and Evaluation of a High Performance Distributed Expert System (HPDES) for Aerospace Ground Verification System”, Workshop on Social Computing and Web Service in conjunction with International Conference on Computational Science, June 2012, USA.
[26] Xiaojun Li, Yang Gao, Ying Liu, “Performance Evaluation of Fast Fourier Transform Application on Heterogeneous Platforms”, International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), October 2011, Beijing, China. 
[27] Shenshen Liang, Ying Liu, Liheng Jian and Yang Gao, “A Utility-based Recommendation Approach for Academic Literatures”, Workshop on Optimization-based Data Mining and Web Intelligence in conjunction with IEEE/WIC/ACM International Conference on Web Intelligence, August 2011, France.
[28] Mingjie Tang, Weihang Wang, Yexi Jiang, Yuanchun Zhou, Jinyan Li, Peng Cui, Ying Liu, Baoping Yan, “Birds Bring Flues? Mining Frequent and High Weighted Cliques from Birds Migration Networks”, 15th International Conference on Database Systems for Advanced Applications, 2010, v 5982 LNCS, PART 2, pp. 359-369.
[29] Xiao Wang, Lingling Zhang, Yuehua Zhang, Ying Liu, Yong Shi, “Software Quality Prediction Models Using the ISBSG Database”, 11th International Symposium on Knowledge and Systems Sciences, September 2010, Xi’an China. 
[30] Shenshen Liang, Ying Liu, Cheng Wang,Liheng Jian, “Design and Evaluation of a Parallel K-Nearest Neighbor Algorithm on CUDA-enabled GPU”, 2nd IEEE Symposium on Web Society, August 2010, Beijing, China.
[31] Xiuxiang Zhao, Yong Shi, Ying Liu, Lingling Zhang, “An Empirical Study of the Influence of Software Trustworthy Attributes to Software Trustworthiness”, 2nd International Conference on Software Engineering and Data Mining, July 2010, Chengdu, China.
[32] Yuehua Zhang, Ying Liu, Lingling Zhang, Yong Shi, “A Data Mining Based Method: Detecting Software Defects in Source Code”, 2nd International Conference on Software Engineering and Data Mining, June 2010, Chengdu, China.
[33] Shenshen Liang, Ying Liu, Cheng Wang and Liheng Jian, “A CUDA-based Parallel Implementation of K-Nearest Neighbor Algorithm”, International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), October 2009, Zhangjiajie, China.
[34] Xiuxiang Zhao, Ying Liu, Yong Shi, “Predicting Software Defects using Multiple Criteria Linear Programming”, International Symposium on Intelligent Information Systems and Applications, October 2009, Qingdao, China. 
[35] Shenshen Liang, Cheng Wang, Ying Liu and Liheng Jian, “CUKNN: A Parallel Implementation of K-Nearest Neighbor on CUDA-enabled GPU”, IEEE Youth Conference on Information, Computing and Telecommunications, September 2009, Beijing, China.
[36] Dengyuan Wu, Ying Liu, Ge Gao, Zhendong Mao, Weishan Ma and Tao He, "An Adaptive Ensemble Classifier for Concept Drifting Stream", IEEE Symposium on Computational Intelligence and Data Mining, March 2009, USA. 
[37] Dengyuan Wu, Ying Liu, Ge Gao, Zhendong Mao, Weishan Ma and Tao He, "C3M: A Classification Model for Multivariate Motion Time Series", CISE2009, Los Angeles, USA. 
[38] Cheng Wang, Ying Liu, Liheng Jian, Peng Zhang, “A Utility-based Web Content Sensitivity Mining Approach”, Workshop on Optimization-based Data Mining and Web Intelligence in conjunction with IEEE/WIC/ACM International Conference on Web Intelligence, December 2008, Sydney, Australia.
[39] Lin Zhou, Ying Liu, Jing Wang, Yong Shi, “Utility-based Web Path Traversal Pattern Mining”, Workshop on High Performance Data Mining in conjunction with IEEE International Conference on Data Mining, October 2007, Omaha, USA.
[40] Ying Liu, Peter Scheuermann, Xingsen Li, Xingquan Zhu, “Using WordNet to Disambiguate Word Senses for Text Classification”, Workshop on Text Data Mining in conjunction with 7th International Conference on Computational Science, May 2007, Beijing, China.
[41] Jing Wang, Ying Liu, Lin Zhou, Yong Shi, Xingquan Zhu, “Pushing Frequency Constraint to Utility Mining Model”, Workshop on High Performance Data Mining in conjunction with 7th International Conference on Computational Science, May 2007, Beijing, China.
[42] Xingsen Li, Yong Shi, Ying Liu, “A Knowledge Management Platform for Optimization-based Data Mining”, Workshop on Optimization-based Data Mining Techniques with Applications in conjunction with 6th IEEE International Conference on Data Mining, December 2006, Hong Kong, China.
[43] Xingsen Li, Ying Liu, Jun Li, Yong Shi, Yuejin Zhang, “A Knowledge Management Model for Middle and Small Enterprises”, 2006 International Conference on Distributed Computing and Applications for Business Engineering and Sciences, October 2006, Hangzhou, China.
[44] Ying Liu, Alok Choudhary, Jianhong Zhou, Ashfaq Khokhar, “A Scalable Distributed Stream Mining System for Highway Traffic Data”, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), September 2006, Berlin, Germany.
[45] Ying Liu, Wei-keng Liao, Alok Choudhary, “A Fast High Utility Itemsets Mining Algorithm”, Workshop on Utility-Based Data Mining in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2005, Chicago, Illinois, USA.
[46] Ying Liu, Wei-keng Liao, Alok Choudhary, “A Two-Phase Algorithm for Fast Discovery of High Utility Itemsets”, 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), May 2005, Hanoi, Vietnam.
[47] Ying Liu, Jayaprakash Pisharath, Wei-keng Liao, Gokhan Memik, Alok Choudhary, Pradeep Dubey, “Performance Evaluation and Characterization of Scalable Data Mining Algorithms”, 16th IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS), pp. 620-625, November 2004, MIT Cambridge, Massachusetts, USA.
[48] Ying Liu, Wei-keng Liao, Alok Choudhary, Steve Chiu, “On-Line Processing Model for Data Mining in Large Scientific Simulations”, 7th Workshop on Mining Scientific and Engineering Datasets in conjunction with SIAM International Conference on Data Mining (SDM), pp. 31-38, April 2004, Lake Buena Vista, Florida, USA.
[49] Wei-keng Liao, Ying Liu, Alok Choudhary, “A Grid-based Clustering Algorithm using Adaptive Mesh Refinement”, 7th Workshop on Mining Scientific and Engineering Datasets in conjunction with SIAM International Conference on Data Mining (SDM), pp. 61-69, April 2004, Lake Buena Vista, Florida, USA.
[50] Ying Liu, Wei-keng Liao, Alok Choudhary, “Design and Evaluation of a Parallel HOP Clustering Algorithm for Cosmological Simulation”, 17th IEEE International Parallel and Distributed Processing Symposium (IPDPS), April 2003, Nice, France.

特邀报告

[1] 《面向研究生的大数据教育》,2018大数据技术大会分论坛,北京,2018.12

[2] 《交通大数据分析算法与应用》,大数据产学研高峰论坛,广州,2018.12

[3] 《基于异构并行计算的大数据分析与挖掘》,CSDN论坛,北京,2018.07

[4] 《基于深度学习的海面舰船识别》,科学数据大会,黑河,2018.07

[5] 《GPU并行计算及其在航天遥测领域的应用》,装备学院,2018.06

[6] 《大数据挖掘在气象领域的应用》,国家气象局,2018.3

[7] 《Big Data Analysis and Applications》,Apec论坛,2017.12

[8] 《基于异构并行计算的大数据分析与挖掘》,大数据产学研高峰论坛,广州,2018.12

[9]《Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning》,GPU/MIC, 贵阳,2017.8

[10]《Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning》,科学数据大会,昆明,2017.08

[11] 《GPU并行计算及其在航天遥测领域的应用》,装备学院,2017.05。

[12] 《基于GPU的高性能数据挖掘》,华为北研所,2016.12。

[13] 《Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning》,大数据产学研高峰论坛,广州,2016.11.

[14]《Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning》, Big Data Analytics Symposium, Beijing, 2016.11

[15]《CUDA-Accelerated Acquisition of Spread Spectrum Signal in Satellite Communication》,GTC China,Beijing, China, 2016.09.

[16] 《基于深度学习的遥感图像舰船分类》,科学数据大会,2016.08.

[17] 《基于GPU的高性能数据挖掘》,中科院软件所,2016.04.

[18]《CUDA-Accelerated Acquisition of Spread Spectrum Signal in Satellite Communication》,Big Data Analytics Forum,Beijing, China, 2015.10.

[19]《CUDA-Accelerated Acquisition of Spread Spectrum Signal in Satellite Communication》,International Workshop on GPU/MIC Solutions to Multiscale Problems in Science and Engineering, 2015.8.
[20] 《An Efficient Parallel Collaborative Filtering Algorithm on Multi-GPU Platform》,GPU Technology Conference, USA, 2015.3.
[21] 《异构云中高性能计算中间件的研究》,第十届两岸三院信息技术与应用交流研讨会,2014.9。
[22]《An Efficient Parallel Collaborative Filtering Algorithm on Multi-GPU Platform》,中国模板计算研讨会,2014.8。
[23] 《An Efficient Parallel Collaborative Filtering Algorithm on Multi-GPU Platform》, International Workshop on GPU/MIC Solutions to Multiscale Problems in Science and Engineering, 2014.8.
[24] 《Big Data Mining》,中国人民大学“大数据·建模方法与传播学研究”暑期工作坊,2014.7。
[25]《Big Data Mining》,CODATA"发展中国家科学大数据国际培训班”,2014.6。
[26] 《大数据》,总参测绘局,2014.4.
[27] 《CUDA-Accelerated Satellite Communication Demodulation》,GPU Technology Conference, USA, 2014.3.
[28]《异构云中高性能计算中间件的研究》,科学数据大会,2014.2。
[29] 《Enabling High Performance Data Intensive and Computation Intensive Applications in Heterogeneous Cloud》, 2013 Chinese-American-German E-Science and Cyberinfrastructure Workshop, 芝加哥,美国,2013.9.
[30] 《CUDA-enabled Multiple Symbol Detection Algorithm in PCM/FM Demodulation》, International Workshop on GPU Solutions to Multiscale Problems in Science and Engineering, 长春,2013.7.
[31] 《Sim-Midware: A Middleware to Enable High Performance ESL Simulation in Heterogeneous Cloud》,Agilent Technologies, 2013.7.
[32] 《大数据与大数据挖掘》,中国科学院计算机网络信息中心,2013.6.
[33] 《基于CUDA架构的并行数据挖掘软件》,2010年中日女科学家研讨会,2010.9.
[34] 《GUCAS_CUMiner: A CUDA-based Parallel Data Mining Toolkit》, 2010 International Workshop on GPU Solutions to Multiscale Problems in Science and Engineering, 2010.7.
[35] 《基于图形处理器的并行计算》,航天部某研究院,2010.6.
[36] 《Utility Mining》, 国立新加坡大学,2010.1.
[37] 《并行计算的新发展》,装备指挥技术学院,2009.6.
[38] 《源代码缺陷挖掘》, 中国科学院软件所/美国马萨诸塞大学联合研讨会,2009.6.
[39] 《基于图形处理器的并行计算》,国家气象局,2009.5.
[40] 《基于图形处理器的并行数据挖掘》,全国高性能计算新浪潮研讨会,2009.5.
[41] 《高性能数据挖掘及应用》,全国虚拟天文台研讨会,2008.11.
[42] 《高性能数据挖掘在科学计算中的应用》,全国科学数据库与信息技术研讨会,2008.10.
[43] 《数据挖掘在审计数据中的应用》,国家审计署,2007.9