Issue No. 08 - Aug. (2013 vol. 25)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2013.99
I want to sincerely thank the 14 associate editors who completed their terms by June 2013: Torsten Grust, Jayant Haritsa, Maurizio Lenzerini, Renee Miller, Srinivasan Parthasarathy, Kian-Lee Tan, Jun Yang, Xiaofang Zhou, Bin Cui, Ravi Kumar, Timos Sellis, and Justin Zobel. They have contributed significantly to the quality and the reputation of TKDE. Without the associate editors, many reviewers, and enormous authors’ joint effort, our journal would not be as good as it is today.
At the same time, I want to formally welcome the associate editors who joined the editorial board in the first half of 2013, Shivnath Babu, Francesco Bonchi, Chee-Yong Chan, Kevin Chang, Sanjay Chawla, Ian Davidson, Ruoming Jin, Panos Kalnis, Xuemin Lin, Dan Olteanu, Naren Ramakrishnan, Mark Sanderson, Ambuj Singh, and Hui Xiong. This group of newly appointed associate editors represents our interest and determination in recruiting the best established and active working experts in the wonderful wide spectrum of knowledge and data engineering. Moreover, they are very committed and dedicated to serving the community and handling the review processes, as testified by their rich experience.
In less than 6 months (1 January to 20 May, 2013), TKDE received 340 original submissions and 134 revised submissions. In the same period, 475 decisions were made and 66 papers (13.9 percent) were accepted, 83 papers (17.5 percent) needed major revisions, and 56 papers (11.8 percent) needed minor revisions. These numbers clearly show that TKDE is a highly preferred and competitive forum for publishing the strongest research outcome in our fields.
The associate editors, the reviewers, and I are working hard to shorten the turn-around time as much as possible without any compromise on quality. For example, 217 of the 340 original submissions (63.8%) submitted between Jan-May 2013 already received a decision. Without the fabulous team of hardworking associate editors and the large base of constructive and responsible reviewers, the review process is simply a mission impossible. Thank you!
Last and not least, I thank all of the authors and readers for your continuing support. You are the ones making TKDE truly meaningful.
Shivnath Babu received the PhD degree from Stanford University in 2005. He is an assistant professor of computer science at Duke University. He has received a US National Science Foundation CAREER Award and three IBM Faculty Awards. His research interests are in ease-of-use and manageability of data-intensive computing systems, automated problem diagnosis and cluster sizing for systems running on cloud platforms, and automated detection and recovery from corruption of data caused by hardware faults, software bugs, or human mistakes.
Francesco Bonchi is a senior research scientist at Yahoo! Research in Barcelona, Spain, where he is the leader of the Web Mining Group. His recent research interests include mining query-logs, social networks, and social media, as well as the privacy issues related to mining these kinds of sensible data. In the past, he has been interested in data mining query languages, constrained pattern mining, mining spatiotemporal and mobility data, and privacy preserving data mining. He is a member of the ECML PKDD Steering Committee, Yahoo! Research ambassador for academic relations with Italy, and the organizer of the Yahoo! Research Barcelona Seminars series. He has been program cochair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010). He is a stable member of the program committees (PC) of all of the main data mining and data bases conferences, often acting as a senior PC member. He has been chair of several workshops and editor of several journal special issues. He is coeditor of the book Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques (Chapman & Hall/CRC Press).
Chee-Yong Chan received the BSc and MSc degrees in computer science from the National University of Singapore (NUS) and the PhD degree in computer science from the University of Wisconsin-Madison. He is an associate professor in the School of Computing, NUS. His research interests are in the area of database management focusing on database usability, query processing and optimization, and database performance. He was a member of technical staff at Bell Labs, Lucent Technologies, from 1999 to 2003 before joining NUS as a faculty member. He is currently an associate editor for the ACM SIGMOD Record and the Proceedings of the VLDB Endowment.
Kevin C. Chang received the BS degree from National Taiwan University and the PhD degree from Stanford University, both in electrical engineering. He is an associate professor of computer science at the University of Illinois at Urbana-Champaign. His research addresses large scale information access, currently focusing on web data-aware search, information integration, and mining. He received a VLDB Best Papers Selection in 2000, a US NSF CAREER Award in 2002, an NCSA Faculty Fellow Award in 2003, IBM Faculty Awards in 2004 and 2005, Academy for Entrepreneurial Leadership Faculty Fellow Award in 2008, and the Incomplete List of Excellent Teachers at the University of Illinois in 2001 and 2004. He loves to bring research results to the real world and, with his students, cofounded Cazoodle, a startup from the University of Illinois, for deepening “data-aware” search over the web.
Sanjay Chawla received the PhD degree in mathematics (1995) from the University of Tennessee, Knoxville. He is a professor of pattern and data mining at the University of Sydney, Australia. In 2012, he was an academic visitor in the Advertising Science Group at Yahoo! Labs, Bangalore, India. He served as the head of school (department chair) of the School of Information Technologies from 2008 to 2011. During 2005-2006, he served as the chief scientist of DTecht, a startup in health insurance surveillance software. He serves on the editorial board of the journal Data Mining and Knowledge Discovery and has been a member of the program committees of leading data mining conferences. He coauthored the textbook Spatial Databases, A Tour (Prentice Hall, 2003), which has also been translated into Chinese and Russian. His research has been recognized by five best paper awards (most recently in 2012).
Ian Davidson received the PhD degree from Monash University, Australia, in 2000 under the supervision of Professor C.S. Wallace, FACM. He was promoted to full professor of computer science at the University of California, Davis, in 2013. He is a recipient of the US NSF CAREER award and has been funded by the US Department of Defense (Office of Naval Research and State Department) as well as industrial gifts from Google, Yahoo!, and IBM for more than $2 Mmillion of grants as the principal investigator. He has published more than 70 papers, and has won several awards, including best paper awards at SIAM Data Mining 2005 (research paper) and the IEEE International Conference on Data Mining 2006 (applied research) as well as best paper nominations at ACM KDD in 2010, 2011, and 2012. He is on the editorial board of the ACM Transactions of Knowledge Discovery and Data Mining and Springer’s Journal of Knowledge Discovery and Data Mining. He is a senior member of the IEEE.
Ruoming Jin received the PhD degree in computer science and engineering from the Ohio State University in 2005. Currently, he is an associate professor at Kent State University. His general research area is in data mining, database, and big data. Recently, his research has focused on graph mining and graph management. He has published more than 90 technical papers in these areas, and most appear in the top data mining and database conferences and journals, including SIGMOD, SIGKDD, ICDM, PVLDB, the ACM Transactions on Database Systems, and the IEEE Transactions on Knowledge and Data Engineering. A few of his papers have been selected as outstanding papers or received best paper nominations. He is also a recipient of the prestigious US NSF CAREER award.
Panos Kalnis received the diploma in computer engineering from the Computer Engineering and Informatics Department, University of Patras, Greece, in 1998 and the PhD degree from the Computer Science Department, Hong Kong University of Science and Technology (HKUST) in 2002. He is an associate professor in the Division of Computer, Electrical and Mathematical Sciences and Engineering at the King Abdullah University of Science and Technology (KAUST). In 2009, he was a visiting assistant professor in the Department of Computer Science, Stanford University. Before that, he was an assistant professor in the Department of Computer Science, National University of Singapore (NUS). In the past, he was involved in the design and testing of VLSI chips at the Computer Technology Institute, Greece. He also worked at several companies on database designing, e-commerce projects, and web applications. He is a regular reviewer and program committee member for all major journals and conferences in databases and data mining, including the ACM Transactions on Database Systems, the IEEE Transactions on Knowledge and Data Engineering, VLDB Journal, the ACM Transactions on Knowledge Discovery from Data, Proceedings of the VLDB Endowment, SIGMOD, SIGKDD, and CIKM. He is also the organizer of the 2013 SIGMOD programming contest. His research interests include databases, cloud computing, distributed systems, large graphs, data privacy, OLAP, mobile databases, and spatiotemporal data.
Xuemin Lin is a professor of computer science and engineering at the University of New South Wales, Australia, and the head of the Database Research Lab. He is a concurrent professor in the School of Software at the East China Normal University under the “Thousand Talents Program.” In recent years, he has published more than 80 papers in top international conferences and top journals in database and data mining areas; in total, he has published more than 200 papers on databases and algorithms in international conferences and international journals. He also coauthored 10 best papers in international conferences, including a best paper at SIGMOD ’11. His current research interests lie in massive data processing, including graph data, spatial temporal data, string data, and uncertain data. Since 2008, he has been serving as an associate editor for the ACM Transactions on Database Systems.
Dan Olteanu received the Dr. rer. nat. degree in computer science from Ludwig Maximilian University in Munich in 2005 and the Dipl. Ing. degree in computer science from the Polytechnic University of Bucharest in 2000. He is a tenured university lecturer (equivalent of associate professor in North America) in the Department of Computer Science at the University of Oxford and a Fellow of St. Cross College. Before joining Oxford, he was a postdoctoral researcher at Saarland University, visiting scientist at Cornell University, and temporary professor at Ruprecht Karl University in Heidelberg. His main research is on system and theoretical aspects of databases and data management, with a current focus on web data, incomplete information, probabilistic databases, data provenance, and factorized databases. He previously served as associate editor of the Proceedings of the VLDB Endowment 2013, PC chair of BNCOD 2013, and as PC member for numerous conferences in his field.
Naren Ramakrishnan received the PhD degree in computer sciences from Purdue University. He is the Thomas L. Phillips Professor of Engineering at Virginia Tech. His research interests focus on mining scientific data sets, with applications to domains such as sustainability, systems biology, neuroscience, health informatics, and intelligence analysis. He directs the Discovery Analytics Center (DAC; http://dac.cs.vt.edu) at Virginia Tech, a university-wide effort that brings together researchers from computer science, statistics, mathematics, and electrical and computer engineering to tackle knowledge discovery problems in important areas of national interest, including intelligence analysis, sustainability, neuroscience, and systems biology. His research has been supported by the US NSF, DHS, NIH, NEH, DARPA, IARPA, ONR, General Motors, HP Labs, NEC Labs, and Advance Auto Parts. He is an ACM Distinguished Scientist (2009).
Mark Sanderson received the BSc (Hons.) and PhD degrees in computer science from the University of Glasgow, Glasgow, United Kingdom, in 1988 and 1997, respectively. From 1998 to 1999, he was a post doctoral researcher at UMass Amherst. Then, he worked as a faculty member in the Information School at the University of Sheffield until 2010. He is a professor in the School of Computer Science and Information Technology at RMIT University, Melbourne, Australia. His interests are in information retrieval and document summarisation. Prof. Sanderson is co-editor of Foundations and TrendsÂ® in Information Retrieval, as well as associate editor of Information Processing and Management and the ACM Transactions on the Web.
Ambuj K. Singh received the BTech degree from the Indian Institute of Technology and the PhD degree from the University of Texas at Austin in 1989. He is a professor of computer science and biomolecular science and engineering at the University of California at Santa Barbara (UCSB). His research interests are in querying and mining of large datasets, especially as they pertain to graphs, networks, high-dimensional, and biological data. He has written more than 180 technical papers in the areas of distributed computing, databases, and bioinformatics and graduated more than 20 PhD students. He has led numerous interdisciplinary projects, and currently leads UCSB’s Information Networks Academic Research Center funded by the ARL. He has served on the editorial boards and program committees of several conferences, workshops, and international meetings
Hui Xiong received the BE degree in automation from the University of Science and Technology of China (USTC), Hefei, China, the MS degree in computer science from the National University of Singapore (NUS), Singapore, and the PhD degree in computer science from the University of Minnesota–Twin Cities, USA, in 2005, He is currently an associate professor in the Management Science and Information Systems Department at Rutgers, the State University of New Jersey, where he received a two-year early promotion/tenure (2009), the Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence (2009), an IBM ESA Innovation Award (2008), the Junior Faculty Teaching Excellence Award (2007), and the Junior Faculty Research Award (2008) at Rutgers Business School. Dr. Xiong’s general area of research is data and knowledge engineering, with a focus on developing effective and efficient data analysis techniques for emerging data intensive applications. His research has been supported in part by the US National Science Foundation (NSF), IBM Research, SAP Corporation, Panasonic USA Inc., and Rutgers University. He has published prolifically in refereed journals and conference proceedings such as the IEEE Transactions on Knowledge and Data Engineering, the VLDB Journal, INFORMS Journal on Computing, the Data Mining and Knowledge Discovery Journal, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), SIAM International Conference on Data Mining (SDM), IEEE International Conference on Data Mining (ICDM), and ACM International Symposium on Advances in Geographic Information Systems (ACM GIS). He is a co-Editor-in-Chief of Encyclopedia of GIS (Springer, 2008). He has served regularly on the organization committees and the program committees of a number of international conferences and workshops, and has also been a reviewer for the leading academic journals in his fields. He is a senior member of the IEEE and a member of the ACM and the ACM SIGKDD.
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