数据挖掘界牛人一览
发信人: mining (May_flowers), 信区: DataMining标 题: 数据挖掘人物介绍系列发信站: 南京大学小百合站 (Sat Sep 4 13:13:01 2004)为了方便大家了解数据挖掘的发展历史，快速把握国际研究动态，跟上国际研究步伐，我将在最近几天整理出一系列国际上研究数据挖掘的牛人的简介、联系方式和个人主页等，希望大家也能够踊跃补充。发信人: mining (Ma
·
发信人: mining (May_flowers), 信区: DataMining
标 题: 数据挖掘人物介绍系列
发信站: 南京大学小百合站 (Sat Sep 4 13:13:01 2004)
为了方便大家了解数据挖掘的发展历史，快速把握国际研究动态，跟上国际研究步
伐，我将在最近几天整理出一系列国际上研究数据挖掘的牛人的简介、联系方式和个人
主页等，希望大家也能够踊跃补充。
发信人: mining (May_flowers), 信区: DataMining
标 题: 数据挖掘人物(Jiawei Han)
发信站: 南京大学小百合站 (Sat Sep 4 13:21:07 2004)
Jiawei Han 个人主页：http://www-sal.cs.uiuc.edu/~hanj/
Professor, Department of Computer Science
Univ. of Illinois at Urbana-Champaign
Rm 2132, Siebel Center for Computer Science
201 N. Goodwin Avenue
Urbana, IL 61801, USA
E-mail: hanj[at]cs.uiuc.edu
Ph.D. (1985), Computer Science, Univ. Wisconsin-Madison
Research Projects
----------------------------------------------------------------------------
----
Mining Sequential and Structured Patterns: Scalability, Flexibility, Extensi
bility and Applicability
This project is to perform a systematic investigation of the principles, alg
orithms, and applications of scalable sequential and structured pattern mini
ng, which covers the following issues: (1) development of highly scalable mi
ning algorithms, including mining max-patterns, closed patterns and top-k pa
tterns; (2) investigation of highly flexible mining methodologies, including
mining of multi-dimensional multi-level sequential and structured patterns
and constraint-based mining; (3) extension of the scope to cover sequential
or structured pattern-based clustering; and (4) application of multi-dimensi
onal, multi-level sequential or structured pattern mining for intrusion dete
ction, Web mining, and other important applications. This will lead to a set
of efficient, scalable, and flexible sequential and structured pattern mini
ng methods for scientific and industrial applications.
----------------------------------------------------------------------------
----
Mining Dynamics of Data Streams in Multi-Dimensional Space
The proposed project is based on our long-term active research, strong resea
rch record, fruitful research results, and rich experience on data mining, d
ata warehousing, database systems, and data mining applications, as well as
our preliminary work on multi-dimensional stream data analysis. Due to the f
ast generation of huge volumes of stream data in many applications, such as
computer network traffic, video surveillance, telecommunication, Web clickin
g stream, stock market, and so on, stream data mining has become an active t
heme of research in data mining, with broad applications in industry and dee
p implications in other related research. This project will perform a system
atic and in-depth investigation on the principles, methods, and implementati
on techniques for mining data stream dynamics, which will lead to deep under
standing of the issues and effective solutions for mining the dynamics of da
ta streams in multi-dimensional space. The project will further advance the
knowledge of the principles, methods, and applications of stream data mining
in particular and data mining in general.
----------------------------------------------------------------------------
----
MAIDS: Mining Alarming Incidents in Data Streams (with NCSA/UIUC)
The MAIDS (Mining Alarming Incidents in Data Streams) project is aimed to pe
rform a systematic investigation of stream data mining principles and algori
thms, develop effective, efficient, and scalable methods for mining the dyna
mics of data streams, and implement a system prototype for online multi-dime
nsional stream data mining applications. This project will develop and imple
ment some new and existing algorithms to discover changes, trends and evolut
ion characteristics in data streams, construct clusters and classification m
odels from data streams, and explore frequent patterns and similarities amon
g data streams. The methods developed by this project will be applied to net
work intrusion detection, telecommunication data flow analysis, credit card
fraud prevention, Web click streams analysis, financial data trend predictio
n, and other applications.
----------------------------------------------------------------------------
----
Mining Database Structures and Linkages
----------------------------------------------------------------------------
----
Spatiotemporal data mining
周志华个人主页：http://cs.nju.edu.cn/people/zhouzh
————————————————————————————————————
周志华，男，1973年11月生。分别于1996年6月、1998年6月和2000年12月于 南京大学
计算机科学与技术系 获学士、硕士和博士学位。2001年1月起留校任教。2002年3月破格
晋升副教授，2003年11月被聘任为教授，2004年4月获博士生导师资格。现任 人工智能
教研室 主任。南京航天航空大学 兼职教授、澳大利亚 Deakin大学 名誉研究员。
目前主要从事机器学习、数据挖掘、模式识别、信息检索、神经计算、进化计算等领域
的研究工作。曾主持或参加过多项国家、省自然科学基金课题的研究工作。发表国际论
文 40余篇。现任国际刊物 Knowledge and Information Systems (Springer出版社) 副
编辑、Artificial Intelligence in Medicine (Elsevier出版社) 和 International
Journal of Data Warehousing and Mining (Idea Group出版社) 编委，以及包括权威
刊物 Artificial Intelligence 和多种IEEE Transactions在内的二十余家国际刊物的
审稿专家，国家自然科学基金委员会信息科学部专家评审组成员，香港研究资助局、荷
兰科学研究基金会 等机构的课题申请评议专家。曾担任 第7届中国机器学习会议 组织
委员会主席、第9届中国机器学习会议 程序委员会共同主席、十余个国际会议程序委员
会委员并多次担任分组会议主席。现任中国计算机学会人工智能与模式识别专业委员会
副主任、中国人工智能学会理事、机器学习专业委员会秘书长、Rough集与软计算专业委
员会副主任，IEEE、IEEE计算机协会 会员。
曾获 微软中国研究院 首届“微软学者”奖 (1999)、首届江苏省优秀硕士学位论文奖(
2001)、 第七届中创软件人才奖 (2002)、江苏省“青蓝工程”优秀青年骨干教师计划
(2002)、第五届全国优秀博士学位论文奖 (2003)、教育部优秀青年教师资助计划 (200
3)、第九届霍英东青年教师基金 (2004)、第六届江苏省优秀科技工作者 (2004)等。20
03年获 国家杰出青年科学基金。
——————————————————————————————————————
Office:
401B, MengMinwei Science Building II, Main Campus of Nanjing University
Nanjing 210093, China
Email:
zhouzh@nju.edu.cn or zhouzh@lamda.nju.edu.cn
Research Interest
My current research interests mainly include machine learning, data mining,
pattern recognition, information retrieval, neural computing, and evolutiona
ry computing
Career
Professor
Department of Computer Science & Technology, Nanjing University, China
Nov. 2003 - present
Associate Professor
Department of Computer Science & Technology, Nanjing University, China
Mar. 2002 - Oct. 2003
Lecturer
Department of Computer Science & Technology, Nanjing University, China
Jan. 2001 - Feb. 2002
Director
AI Lab, Department of Computer Science & Technology, Nanjing University, China
May 2002 - present
Visiting Professor
Intelligent Information Processing Laboratory, Fudan University, China
Mar.2004 - Apr. 2004
Visiting Scholar
Academy of Mathematics and Systems Sciences, CAS, China
Mar.2003 - Apr. 2003
Visiting Research Fellow
School of Computing & Mathematics, Deakin University, Australia
this school was re-named as School of Information Technology in Jan.2003
Jun.2002 - Aug. 2002
Adjunct Professor
Nanjing University of Aeronautics and Astronautics, China
Jun.2004 - present
Honorary Fellow
Deakin University, Australia
Nov.2002 - present
--
※ 来源:．南京大学小百合站 bbs.nju.edu.cn．[FROM: 202.118.237.18]
--
※ 来源:．南京大学小百合站 bbs.nju.edu.cn．[FROM: 202.118.237.18]
发信人: NAOMIELIE (雁来红), 信区: DataMining
标 题: Re: 建议斑竹把数据挖掘人物整理一下置顶
发信站: 南京大学小百合站 (Wed Sep 22 18:58:04 2004)
It's really hard to identify if a researcher is a 'data mining guy'.
:-)
Many people from algorithm, db, machine learning communities should be include
d
in the list if we define 'people who have high-quality data mining papers publ
ished' as 'dm guy'. If the list is too long, it is meaningless to help us to f
ind information. :-(
Maybe, we should attach some 'keywords' to each name, so that we know what he/
she is/was doing. But if we do this, the list would be very complicated.
Some people that I recommend to be added to the list are as follows:
Jon Kleinberg (link analysis, clustering, ...)
http://www.cs.cornell.edu/home/kleinber/
Jeffrey Ullman (rule mining, ...)
(his DM course is interesting, and it's said that he is writing a dm book)
http://www-db.stanford.edu/~ullman/
S. Muthu Muthukrishnan: online algorithms for mining
http://www.cs.rutgers.edu/~muthu/
Rajeev Motwani: online algorithms for mining
http://theory.stanford.edu/~rajeev/
Rajeev Rastogi: classification, clustering, rule mining, ...
http://www.bell-labs.com/user/rastogi/
Christos Faloutsos: time-series mining, graph mining, ...
http://www-2.cs.cmu.edu/~christos/
...
To list all people is a giant project. *_-
我想数据挖掘的前途就象那早晨的太阳,一定会有照耀世界的时候.
2005-6-26 12:35 PM #1
weilaiyxj
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________________________________________
[这个贴子最后由 weilaiyxj 在 2005年06月27日 19:26 重新编辑]http://www.kmining.com/info_people.html
Business Intelligence, KDD and Data Mining People
If you find any broken links or want to add yourself - please e-mail!
Name
Organization Country
Abraham Meidan WizSoft Israel
Achim Hoffmann University of New South Wales Australia
Akira Shimazu Japan Advanced Institute of Science and Technology Japan
Aleksandar Lazarević University of Minnesota USA
Alok Choudhary Northwestern University USA
AnHai Doan University Illinois Urbana USA
Anoop Singhal Monmouth University USA
Assaf Schuster Israel Institute of Technology Israel
Bart Goethals University of Antwerp Belgium
Benjamin W. Wah University of Illinois USA
Bo Zhang Tsinghua University China
Boonserm Kijsirikul Chulalongkorn University Thailand
Carla E. Brodley Tufts University USA
Charles Elkan University of California USA
Chengqi Zhang University of Technology Sydney Australia
Chris Ding Lawrence Berkeley National Laboratory USA
Christian Borgelt Otto-von-Guericke-University of Magdeburg Germany
Christopher W. Clifton Purdue University USA
Daniel Boley University of Minnesota USA
David J. Hand Imperial College UK
David Skillicorn Queen's University Canada
Deepak K. Agarwal AT&T Labs USA
Dennis D. Cox Rice University USA
Dharmendra S. Modha IBM Almaden Research Center USA
Dimitrios Gunopulos University of California USA
Dino Pedreschi University of Pisa Italy
Djamel A. Zighed University Lyon 2 France
Doheon Lee Korea Advanced Institute of Science and Technology Korea
Domenico Talia Universit? della Calabria Italy
Ee-Peng Lim University of Minnesota USA
Eibe Frank University of Waikato New Zealand
El-Ghazali Talbi Universit? des Sciences et Technologies de Lille France
Ferenc Bodon Budapest University of Technology and Economics Hungary
Floriana Esposito University of Bari Italy
Gabriele Kern-Isberner University of Dortmunt Germany
Geoffrey I. Webb Monash University Australia
George Karypis University of Minnesota USA
Graham J. Williams Australian Taxation Office Australia
Greg Ridgeway RAND Statistics Group USA
Gregory Piatetsky-Shapiro KDnuggets USA
Guozhu Dong Wright State University USA
G鰏ta Grahne Concordia University Canada
Haesun Park University of Minnesota USA
Haixun Wang IBM T. J. Watson Research Center USA
Hannu T.T. Toivonen University of Helsinki Finland
Heikki Mannila Helsinki University of Technology Finland
Hillol Kargupta University of Maryland USA
Hiroki Arimura Hokkaido University Japan
Hiroshi Motoda Osaka University Japan
Hiroyuki Kawano Nanzan University Japan
Honghua Dai Deakin University Australia
Hongjun Lu Hong Kong University of Science and Technology China
Huan Liu Arizona State University USA
Inderjit S. Dhillon University of Texas USA
Jacob Kogan University of Maryland USA
Jan Rauch University of Economics Czech Republic
Jean-Fran鏾is Boulicaut Institut National des Sciences Appliqu閑s de Lyon France
Jeffrey D. Ullman Stanford University USA
Jes鷖 S. Aguilar-Ruiz University of Seville Spain
Jian Pei University at Buffalo USA
Jiawei Han University of Illinois USA
Jinyan Li Institute for Infocomm Research Singapore
Jo鉶 Gama University of Porto Portugal
Johannes Gehrke Cornell University USA
Jonathan Lawry University of Bristol UK
Jongwoo Jeon Seoul National University Korea
Katharina Morik University of Dortmund Germany
Kenji Satou Japan Advanced Institute of Science and Technology Japan
Kevin H. Knuth NASA Ames Research Center USA
Krishnamoorthy Sivakumar Washington State University USA
Kwang Hyung Lee Korea Advanced Institute of Science and Technology Korea
Kyu-Young Whang Korea Advanced Institute of Science and Technology Korea
Kyuseok Shim Seoul National University Korea
Laurentiu Cristofor The University of Massachusetts Boston USA
Ljupco Todorovski Jozef Stefan Institute Slovenia
Luc De Raedt University of Freiburg Germany
Manoranjan Dash Nanyang Technological University Singapore
Marek Wojciechowski Poznan University of Technology Poland
Marina Meila University of Washington USA
Marko Grobelnik J. Stefan Institute Slovenia
Masaru Kitsuregawa University of Tokyo Japan
Masashi Shimbo Nara Institute of Science and Technology Japan
Mehran Sahami Stanford University USA
Michael C. Burl Jet Propulsion Laboratory USA
Michael May Fraunhofer Institute for Autonomous Intelligent Systems Germany
Michael R. Berthold University of Konstanz Germany
Mich鑜e Sebag University Paris Orsay France
Mihael Ankerst Allianz Germany
Mikolaj Morzy Poznan University of Technology Poland
Ming-Syan Chen National Taiwan University Taiwan
Minos N. Garofalakis Bell Laboratories USA
Mohammed J. Zaki Rensselaer Polytechnic Institute US
Monique Noirhomme University of Notre Dame de la Parix Belgium
Myoung Ho Kim Korea Advanced Institute of Science and Technology Korea
Myra Spiliopoulou Humboldt-University of Berlin Germany
Nada Lavrac Jozef Stefan Institute Slovenia
Nicholas Cercone Dalhousie University Canada
Nicolas Pasquier I3S Laboratory France
Nina Mishra Hewlett-Packard Laboratories USA
Ning Zhong Maebashi Institute of Technology Japan
Olfa Nasraoui University of Louisville USA
Pavel Brazdil University of Porto Portugal
Peter A. Flach University of Bristol UK
Peter Haddawy Asian Institute of Technology Thailand
Peter Scheuermann Northwestern University USA
Philip S. Yu IBM T.J. Watson Research Center USA
Pradeep Dubey Stony Brook University USA
Raghu Ramakrishnan University of Wisconsin USA
Rajeev Motwani Stanford University USA
Rajeev Rastogi Bell Laboratories USA
Rao Kotagiri University of Melbourne Australia
Robert Cooley KXEN USA
Robert Grossman University of Illinios USA
Roberto Bayardo IBM Almaden Research Center USA
Ronen Feldman Bar-Ilan University Israel
Rong Jin Michigan State University USA
Rudy Setiono National University of Singapore Singapore
S. Muthu Muthukrishnan Rutgers University USA
Saharon Rosset IBM T.J. Watson Research Center USA
San-Yih Hwang National Sun Yat-Sen University Taiwan
Saso Dzeroski Jozef Stefan Institute Slovenia
Se June Hong IBM T.J. Watson Research Center USA
Seiji Yamada National Institute of Informatics Japan
Sharad Mehrotra University of California USA
Sharma Chakravarthy The University of Texas at Arlington USA
Shashi Shekhar University of Minnesota USA
Shawn Newsam CASC USA
Shusaku Tsumoto Shimane University School of Medicine Japan
Shyam Kumar Gupta Indian Institute of Technology Delhi India
Simeon J. Simoff University of Technology Sydney Australia
Siu Cheung Hui Nanyang Technological University Singapore
Srinivasan Parthasarathy The Ohio State University USA
Sudipto Guha University of Pennsylvania USA
Sunita Sarawagi Indian Institute of Technology India
Sven F. Crone Lancaster University Management School UK
Tadinada Venkata Prabhakar Indian Institute of Technology Kanpur India
Takahira Yamaguchi Keio University Japan
Takao Terano Tsukuba University Japan
Takashi Okada Kwansei Gakuin University Japan
Takashi Washio Osaka University Japan
Takeaki Uno National Institute of Informatics Japan
Takehisa Yairi University of Tokyo Japan
Tapio Elomaa Tampere University of Technology Finland
Tetsuya Murai Hokkaido University Japan
Tom Mitchell Carnegie Mellon University USA
Tru Hoang Cao Ho Chi Minh City University of Technology Vietnam
Tsau Young Lin San Jose State University USA
Tu Bao Ho Japan Advanced Institute of Science and Technology Japan
Vasilis Megalooikonomou Temple University USA
Vikram Pudi International Institute of Information Technology India
Vipin Kumar University of Minnesota USA
Vo Ngoc Anh University of Melbourne Australia
Walter Kosters Universiteit Leiden The Netherlands
Wee Keong Ng Nanyang Technological University Singapore
Wei Fan Columbia University USA
Wenliang Du Syracuse University USA
Werner Stuetzle University of Washington USA
Wray Buntine Helsinki Institute for Information Technology Finland
Wynne Hsu National University of Singapore Singapore
Xindong Wu University of Vermont USA
Yannis Manolopoulos Aristotle University of Thessaloniki Greece
Yasuhiko Kitamura Kwansei Gakuin University Japan
Yi Lin University of Wisconsin USA
Yiyu Yao University of Regina Canada
Yoon-Joon Lee Korea Advanced Institute of Science and Technology Korea
Yoshiteru Nakamori Japan Advanced Institute of Science and Technology Japan
Yuedong Wang University of California USA
Yuji Matsumoto Nara Institute of Science and Technology Japan
Zaiqing Nie Microsoft Research Asia China
Zhi-Hua Zhou Nanjing University China
Zoran Obradovic Temple University USA
标 题: 数据挖掘人物介绍系列
发信站: 南京大学小百合站 (Sat Sep 4 13:13:01 2004)
为了方便大家了解数据挖掘的发展历史，快速把握国际研究动态，跟上国际研究步
伐，我将在最近几天整理出一系列国际上研究数据挖掘的牛人的简介、联系方式和个人
主页等，希望大家也能够踊跃补充。
发信人: mining (May_flowers), 信区: DataMining
标 题: 数据挖掘人物(Jiawei Han)
发信站: 南京大学小百合站 (Sat Sep 4 13:21:07 2004)
Jiawei Han 个人主页：http://www-sal.cs.uiuc.edu/~hanj/
Professor, Department of Computer Science
Univ. of Illinois at Urbana-Champaign
Rm 2132, Siebel Center for Computer Science
201 N. Goodwin Avenue
Urbana, IL 61801, USA
E-mail: hanj[at]cs.uiuc.edu
Ph.D. (1985), Computer Science, Univ. Wisconsin-Madison
Research Projects
----------------------------------------------------------------------------
----
Mining Sequential and Structured Patterns: Scalability, Flexibility, Extensi
bility and Applicability
This project is to perform a systematic investigation of the principles, alg
orithms, and applications of scalable sequential and structured pattern mini
ng, which covers the following issues: (1) development of highly scalable mi
ning algorithms, including mining max-patterns, closed patterns and top-k pa
tterns; (2) investigation of highly flexible mining methodologies, including
mining of multi-dimensional multi-level sequential and structured patterns
and constraint-based mining; (3) extension of the scope to cover sequential
or structured pattern-based clustering; and (4) application of multi-dimensi
onal, multi-level sequential or structured pattern mining for intrusion dete
ction, Web mining, and other important applications. This will lead to a set
of efficient, scalable, and flexible sequential and structured pattern mini
ng methods for scientific and industrial applications.
----------------------------------------------------------------------------
----
Mining Dynamics of Data Streams in Multi-Dimensional Space
The proposed project is based on our long-term active research, strong resea
rch record, fruitful research results, and rich experience on data mining, d
ata warehousing, database systems, and data mining applications, as well as
our preliminary work on multi-dimensional stream data analysis. Due to the f
ast generation of huge volumes of stream data in many applications, such as
computer network traffic, video surveillance, telecommunication, Web clickin
g stream, stock market, and so on, stream data mining has become an active t
heme of research in data mining, with broad applications in industry and dee
p implications in other related research. This project will perform a system
atic and in-depth investigation on the principles, methods, and implementati
on techniques for mining data stream dynamics, which will lead to deep under
standing of the issues and effective solutions for mining the dynamics of da
ta streams in multi-dimensional space. The project will further advance the
knowledge of the principles, methods, and applications of stream data mining
in particular and data mining in general.
----------------------------------------------------------------------------
----
MAIDS: Mining Alarming Incidents in Data Streams (with NCSA/UIUC)
The MAIDS (Mining Alarming Incidents in Data Streams) project is aimed to pe
rform a systematic investigation of stream data mining principles and algori
thms, develop effective, efficient, and scalable methods for mining the dyna
mics of data streams, and implement a system prototype for online multi-dime
nsional stream data mining applications. This project will develop and imple
ment some new and existing algorithms to discover changes, trends and evolut
ion characteristics in data streams, construct clusters and classification m
odels from data streams, and explore frequent patterns and similarities amon
g data streams. The methods developed by this project will be applied to net
work intrusion detection, telecommunication data flow analysis, credit card
fraud prevention, Web click streams analysis, financial data trend predictio
n, and other applications.
----------------------------------------------------------------------------
----
Mining Database Structures and Linkages
----------------------------------------------------------------------------
----
Spatiotemporal data mining
周志华个人主页：http://cs.nju.edu.cn/people/zhouzh
————————————————————————————————————
周志华，男，1973年11月生。分别于1996年6月、1998年6月和2000年12月于 南京大学
计算机科学与技术系 获学士、硕士和博士学位。2001年1月起留校任教。2002年3月破格
晋升副教授，2003年11月被聘任为教授，2004年4月获博士生导师资格。现任 人工智能
教研室 主任。南京航天航空大学 兼职教授、澳大利亚 Deakin大学 名誉研究员。
目前主要从事机器学习、数据挖掘、模式识别、信息检索、神经计算、进化计算等领域
的研究工作。曾主持或参加过多项国家、省自然科学基金课题的研究工作。发表国际论
文 40余篇。现任国际刊物 Knowledge and Information Systems (Springer出版社) 副
编辑、Artificial Intelligence in Medicine (Elsevier出版社) 和 International
Journal of Data Warehousing and Mining (Idea Group出版社) 编委，以及包括权威
刊物 Artificial Intelligence 和多种IEEE Transactions在内的二十余家国际刊物的
审稿专家，国家自然科学基金委员会信息科学部专家评审组成员，香港研究资助局、荷
兰科学研究基金会 等机构的课题申请评议专家。曾担任 第7届中国机器学习会议 组织
委员会主席、第9届中国机器学习会议 程序委员会共同主席、十余个国际会议程序委员
会委员并多次担任分组会议主席。现任中国计算机学会人工智能与模式识别专业委员会
副主任、中国人工智能学会理事、机器学习专业委员会秘书长、Rough集与软计算专业委
员会副主任，IEEE、IEEE计算机协会 会员。
曾获 微软中国研究院 首届“微软学者”奖 (1999)、首届江苏省优秀硕士学位论文奖(
2001)、 第七届中创软件人才奖 (2002)、江苏省“青蓝工程”优秀青年骨干教师计划
(2002)、第五届全国优秀博士学位论文奖 (2003)、教育部优秀青年教师资助计划 (200
3)、第九届霍英东青年教师基金 (2004)、第六届江苏省优秀科技工作者 (2004)等。20
03年获 国家杰出青年科学基金。
——————————————————————————————————————
Office:
401B, MengMinwei Science Building II, Main Campus of Nanjing University
Nanjing 210093, China
Email:
zhouzh@nju.edu.cn or zhouzh@lamda.nju.edu.cn
Research Interest
My current research interests mainly include machine learning, data mining,
pattern recognition, information retrieval, neural computing, and evolutiona
ry computing
Career
Professor
Department of Computer Science & Technology, Nanjing University, China
Nov. 2003 - present
Associate Professor
Department of Computer Science & Technology, Nanjing University, China
Mar. 2002 - Oct. 2003
Lecturer
Department of Computer Science & Technology, Nanjing University, China
Jan. 2001 - Feb. 2002
Director
AI Lab, Department of Computer Science & Technology, Nanjing University, China
May 2002 - present
Visiting Professor
Intelligent Information Processing Laboratory, Fudan University, China
Mar.2004 - Apr. 2004
Visiting Scholar
Academy of Mathematics and Systems Sciences, CAS, China
Mar.2003 - Apr. 2003
Visiting Research Fellow
School of Computing & Mathematics, Deakin University, Australia
this school was re-named as School of Information Technology in Jan.2003
Jun.2002 - Aug. 2002
Adjunct Professor
Nanjing University of Aeronautics and Astronautics, China
Jun.2004 - present
Honorary Fellow
Deakin University, Australia
Nov.2002 - present
--
※ 来源:．南京大学小百合站 bbs.nju.edu.cn．[FROM: 202.118.237.18]
--
※ 来源:．南京大学小百合站 bbs.nju.edu.cn．[FROM: 202.118.237.18]
发信人: NAOMIELIE (雁来红), 信区: DataMining
标 题: Re: 建议斑竹把数据挖掘人物整理一下置顶
发信站: 南京大学小百合站 (Wed Sep 22 18:58:04 2004)
It's really hard to identify if a researcher is a 'data mining guy'.
:-)
Many people from algorithm, db, machine learning communities should be include
d
in the list if we define 'people who have high-quality data mining papers publ
ished' as 'dm guy'. If the list is too long, it is meaningless to help us to f
ind information. :-(
Maybe, we should attach some 'keywords' to each name, so that we know what he/
she is/was doing. But if we do this, the list would be very complicated.
Some people that I recommend to be added to the list are as follows:
Jon Kleinberg (link analysis, clustering, ...)
http://www.cs.cornell.edu/home/kleinber/
Jeffrey Ullman (rule mining, ...)
(his DM course is interesting, and it's said that he is writing a dm book)
http://www-db.stanford.edu/~ullman/
S. Muthu Muthukrishnan: online algorithms for mining
http://www.cs.rutgers.edu/~muthu/
Rajeev Motwani: online algorithms for mining
http://theory.stanford.edu/~rajeev/
Rajeev Rastogi: classification, clustering, rule mining, ...
http://www.bell-labs.com/user/rastogi/
Christos Faloutsos: time-series mining, graph mining, ...
http://www-2.cs.cmu.edu/~christos/
...
To list all people is a giant project. *_-
我想数据挖掘的前途就象那早晨的太阳,一定会有照耀世界的时候.
2005-6-26 12:35 PM #1
weilaiyxj
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Name
Organization Country
Abraham Meidan WizSoft Israel
Achim Hoffmann University of New South Wales Australia
Akira Shimazu Japan Advanced Institute of Science and Technology Japan
Aleksandar Lazarević University of Minnesota USA
Alok Choudhary Northwestern University USA
AnHai Doan University Illinois Urbana USA
Anoop Singhal Monmouth University USA
Assaf Schuster Israel Institute of Technology Israel
Bart Goethals University of Antwerp Belgium
Benjamin W. Wah University of Illinois USA
Bo Zhang Tsinghua University China
Boonserm Kijsirikul Chulalongkorn University Thailand
Carla E. Brodley Tufts University USA
Charles Elkan University of California USA
Chengqi Zhang University of Technology Sydney Australia
Chris Ding Lawrence Berkeley National Laboratory USA
Christian Borgelt Otto-von-Guericke-University of Magdeburg Germany
Christopher W. Clifton Purdue University USA
Daniel Boley University of Minnesota USA
David J. Hand Imperial College UK
David Skillicorn Queen's University Canada
Deepak K. Agarwal AT&T Labs USA
Dennis D. Cox Rice University USA
Dharmendra S. Modha IBM Almaden Research Center USA
Dimitrios Gunopulos University of California USA
Dino Pedreschi University of Pisa Italy
Djamel A. Zighed University Lyon 2 France
Doheon Lee Korea Advanced Institute of Science and Technology Korea
Domenico Talia Universit? della Calabria Italy
Ee-Peng Lim University of Minnesota USA
Eibe Frank University of Waikato New Zealand
El-Ghazali Talbi Universit? des Sciences et Technologies de Lille France
Ferenc Bodon Budapest University of Technology and Economics Hungary
Floriana Esposito University of Bari Italy
Gabriele Kern-Isberner University of Dortmunt Germany
Geoffrey I. Webb Monash University Australia
George Karypis University of Minnesota USA
Graham J. Williams Australian Taxation Office Australia
Greg Ridgeway RAND Statistics Group USA
Gregory Piatetsky-Shapiro KDnuggets USA
Guozhu Dong Wright State University USA
G鰏ta Grahne Concordia University Canada
Haesun Park University of Minnesota USA
Haixun Wang IBM T. J. Watson Research Center USA
Hannu T.T. Toivonen University of Helsinki Finland
Heikki Mannila Helsinki University of Technology Finland
Hillol Kargupta University of Maryland USA
Hiroki Arimura Hokkaido University Japan
Hiroshi Motoda Osaka University Japan
Hiroyuki Kawano Nanzan University Japan
Honghua Dai Deakin University Australia
Hongjun Lu Hong Kong University of Science and Technology China
Huan Liu Arizona State University USA
Inderjit S. Dhillon University of Texas USA
Jacob Kogan University of Maryland USA
Jan Rauch University of Economics Czech Republic
Jean-Fran鏾is Boulicaut Institut National des Sciences Appliqu閑s de Lyon France
Jeffrey D. Ullman Stanford University USA
Jes鷖 S. Aguilar-Ruiz University of Seville Spain
Jian Pei University at Buffalo USA
Jiawei Han University of Illinois USA
Jinyan Li Institute for Infocomm Research Singapore
Jo鉶 Gama University of Porto Portugal
Johannes Gehrke Cornell University USA
Jonathan Lawry University of Bristol UK
Jongwoo Jeon Seoul National University Korea
Katharina Morik University of Dortmund Germany
Kenji Satou Japan Advanced Institute of Science and Technology Japan
Kevin H. Knuth NASA Ames Research Center USA
Krishnamoorthy Sivakumar Washington State University USA
Kwang Hyung Lee Korea Advanced Institute of Science and Technology Korea
Kyu-Young Whang Korea Advanced Institute of Science and Technology Korea
Kyuseok Shim Seoul National University Korea
Laurentiu Cristofor The University of Massachusetts Boston USA
Ljupco Todorovski Jozef Stefan Institute Slovenia
Luc De Raedt University of Freiburg Germany
Manoranjan Dash Nanyang Technological University Singapore
Marek Wojciechowski Poznan University of Technology Poland
Marina Meila University of Washington USA
Marko Grobelnik J. Stefan Institute Slovenia
Masaru Kitsuregawa University of Tokyo Japan
Masashi Shimbo Nara Institute of Science and Technology Japan
Mehran Sahami Stanford University USA
Michael C. Burl Jet Propulsion Laboratory USA
Michael May Fraunhofer Institute for Autonomous Intelligent Systems Germany
Michael R. Berthold University of Konstanz Germany
Mich鑜e Sebag University Paris Orsay France
Mihael Ankerst Allianz Germany
Mikolaj Morzy Poznan University of Technology Poland
Ming-Syan Chen National Taiwan University Taiwan
Minos N. Garofalakis Bell Laboratories USA
Mohammed J. Zaki Rensselaer Polytechnic Institute US
Monique Noirhomme University of Notre Dame de la Parix Belgium
Myoung Ho Kim Korea Advanced Institute of Science and Technology Korea
Myra Spiliopoulou Humboldt-University of Berlin Germany
Nada Lavrac Jozef Stefan Institute Slovenia
Nicholas Cercone Dalhousie University Canada
Nicolas Pasquier I3S Laboratory France
Nina Mishra Hewlett-Packard Laboratories USA
Ning Zhong Maebashi Institute of Technology Japan
Olfa Nasraoui University of Louisville USA
Pavel Brazdil University of Porto Portugal
Peter A. Flach University of Bristol UK
Peter Haddawy Asian Institute of Technology Thailand
Peter Scheuermann Northwestern University USA
Philip S. Yu IBM T.J. Watson Research Center USA
Pradeep Dubey Stony Brook University USA
Raghu Ramakrishnan University of Wisconsin USA
Rajeev Motwani Stanford University USA
Rajeev Rastogi Bell Laboratories USA
Rao Kotagiri University of Melbourne Australia
Robert Cooley KXEN USA
Robert Grossman University of Illinios USA
Roberto Bayardo IBM Almaden Research Center USA
Ronen Feldman Bar-Ilan University Israel
Rong Jin Michigan State University USA
Rudy Setiono National University of Singapore Singapore
S. Muthu Muthukrishnan Rutgers University USA
Saharon Rosset IBM T.J. Watson Research Center USA
San-Yih Hwang National Sun Yat-Sen University Taiwan
Saso Dzeroski Jozef Stefan Institute Slovenia
Se June Hong IBM T.J. Watson Research Center USA
Seiji Yamada National Institute of Informatics Japan
Sharad Mehrotra University of California USA
Sharma Chakravarthy The University of Texas at Arlington USA
Shashi Shekhar University of Minnesota USA
Shawn Newsam CASC USA
Shusaku Tsumoto Shimane University School of Medicine Japan
Shyam Kumar Gupta Indian Institute of Technology Delhi India
Simeon J. Simoff University of Technology Sydney Australia
Siu Cheung Hui Nanyang Technological University Singapore
Srinivasan Parthasarathy The Ohio State University USA
Sudipto Guha University of Pennsylvania USA
Sunita Sarawagi Indian Institute of Technology India
Sven F. Crone Lancaster University Management School UK
Tadinada Venkata Prabhakar Indian Institute of Technology Kanpur India
Takahira Yamaguchi Keio University Japan
Takao Terano Tsukuba University Japan
Takashi Okada Kwansei Gakuin University Japan
Takashi Washio Osaka University Japan
Takeaki Uno National Institute of Informatics Japan
Takehisa Yairi University of Tokyo Japan
Tapio Elomaa Tampere University of Technology Finland
Tetsuya Murai Hokkaido University Japan
Tom Mitchell Carnegie Mellon University USA
Tru Hoang Cao Ho Chi Minh City University of Technology Vietnam
Tsau Young Lin San Jose State University USA
Tu Bao Ho Japan Advanced Institute of Science and Technology Japan
Vasilis Megalooikonomou Temple University USA
Vikram Pudi International Institute of Information Technology India
Vipin Kumar University of Minnesota USA
Vo Ngoc Anh University of Melbourne Australia
Walter Kosters Universiteit Leiden The Netherlands
Wee Keong Ng Nanyang Technological University Singapore
Wei Fan Columbia University USA
Wenliang Du Syracuse University USA
Werner Stuetzle University of Washington USA
Wray Buntine Helsinki Institute for Information Technology Finland
Wynne Hsu National University of Singapore Singapore
Xindong Wu University of Vermont USA
Yannis Manolopoulos Aristotle University of Thessaloniki Greece
Yasuhiko Kitamura Kwansei Gakuin University Japan
Yi Lin University of Wisconsin USA
Yiyu Yao University of Regina Canada
Yoon-Joon Lee Korea Advanced Institute of Science and Technology Korea
Yoshiteru Nakamori Japan Advanced Institute of Science and Technology Japan
Yuedong Wang University of California USA
Yuji Matsumoto Nara Institute of Science and Technology Japan
Zaiqing Nie Microsoft Research Asia China
Zhi-Hua Zhou Nanjing University China
Zoran Obradovic Temple University USA
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