D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 38 Citations 6,062 140 World Ranking 5031 National Ranking 2478

Research.com Recognitions

Awards & Achievements

2010 - ACM Distinguished Member

2007 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Artificial intelligence
  • Algorithm

Bitmap index, Bitmap, Algorithm, Data mining and Search engine indexing are his primary areas of study. Information retrieval covers Kesheng Wu research in Bitmap index. He interconnects Storage model, Data warehouse and Code in the investigation of issues within Bitmap.

His work deals with themes such as Lanczos resampling, Eigenvalues and eigenvectors and Lanczos algorithm, which intersect with Algorithm. In general Data mining, his work in Data visualization and Data stream mining is often linked to Software framework, Scale and Process linking many areas of study. His Database index study in the realm of Search engine indexing connects with subjects such as Uncompressed video and Bottleneck.

His most cited work include:

  • Higher-order finite-difference pseudopotential method: An application to diatomic molecules (365 citations)
  • Optimizing bitmap indices with efficient compression (280 citations)
  • Thick-Restart Lanczos Method for Large Symmetric Eigenvalue Problems (240 citations)

What are the main themes of his work throughout his whole career to date?

Kesheng Wu mainly investigates Data mining, Search engine indexing, Bitmap, Bitmap index and Algorithm. His Data mining study incorporates themes from Scalability, Set and Index. The Search engine indexing study combines topics in areas such as Database, Hierarchical Data Format and Parallel computing.

The concepts of his Bitmap study are interwoven with issues in Cardinality, Code, Bin, Data warehouse and Speedup. His Bitmap index study integrates concerns from other disciplines, such as Data compression and Projection. His Algorithm research is multidisciplinary, relying on both Lanczos resampling, Eigenvalues and eigenvectors and Data structure.

He most often published in these fields:

  • Data mining (35.20%)
  • Search engine indexing (23.47%)
  • Bitmap (22.96%)

What were the highlights of his more recent work (between 2017-2020)?

  • Supercomputer (6.63%)
  • Distributed computing (5.61%)
  • Hierarchical Data Format (8.67%)

In recent papers he was focusing on the following fields of study:

Kesheng Wu mostly deals with Supercomputer, Distributed computing, Hierarchical Data Format, Data transmission and Set. His Supercomputer course of study focuses on Performance prediction and Heuristics, Host, Throughput and Network monitoring. Kesheng Wu works mostly in the field of Heuristics, limiting it down to concerns involving Big data and, occasionally, Information retrieval, Cardinality, Data set and NetCDF.

Kesheng Wu combines subjects such as Workload, Analytics, Raw data and FLOPS with his study of Distributed computing. His Hierarchical Data Format research incorporates elements of Data access, Scalability and Data management. His research in Data access intersects with topics in Lustre, Hierarchical storage management, Bitmap index, Data structure and Synthetic data.

Between 2017 and 2020, his most popular works were:

  • ArrayBridge: Interweaving Declarative Array Processing in SciDB with Imperative HDF5-Based Programs (8 citations)
  • ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage (7 citations)
  • Parallel membership queries on very large scientific data sets using bitmap indexes (7 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Quantum mechanics
  • Artificial intelligence

His scientific interests lie mostly in Hierarchical Data Format, Distributed computing, Supercomputer, Data access and Set. His studies deal with areas such as Scalability, File format, Data management and Pipeline as well as Hierarchical Data Format. The study incorporates disciplines such as Lustre, Hierarchical storage management, Performance prediction, Provisioning and Data structure in addition to Distributed computing.

His Supercomputer research is multidisciplinary, incorporating elements of Scheme, System software, Task and Distributed File System. The Data access study combines topics in areas such as NetCDF, Data set, Bitmap index, Synthetic data and Big data. Kesheng Wu interconnects Intrusion detection system, Artificial intelligence and Computer network, Network security in the investigation of issues within Set.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Higher-order finite-difference pseudopotential method: An application to diatomic molecules

James R. Chelikowsky;N. Troullier;K. Wu;Yousef Saad.
Physical Review B (1994)

581 Citations

Optimizing bitmap indices with efficient compression

Kesheng Wu;Ekow J. Otoo;Arie Shoshani.
ACM Transactions on Database Systems (2006)

427 Citations

Fast connected-component labeling

Lifeng He;Yuyan Chao;Kenji Suzuki;Kesheng Wu.
Pattern Recognition (2009)

370 Citations

Thick-Restart Lanczos Method for Large Symmetric Eigenvalue Problems

Kesheng Wu;Horst Simon.
SIAM Journal on Matrix Analysis and Applications (2000)

355 Citations

Optimizing two-pass connected-component labeling algorithms

Kesheng Wu;Ekow Otoo;Kenji Suzuki.
Pattern Analysis and Applications (2009)

287 Citations

On the performance of bitmap indices for high cardinality attributes

Kesheng Wu;Ekow Otoo;Arie Shoshani.
very large data bases (2004)

241 Citations

Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks

Qing Liu;Jeremy Logan;Yuan Tian;Hasan Abbasi.
Concurrency and Computation: Practice and Experience (2014)

220 Citations

FastBit: interactively searching massive data

K. Wu;S. Ahern;E. W. Bethel;E. W. Bethel;J. Chen.
Lawrence Berkeley National Laboratory (2009)

195 Citations

Compressing bitmap indexes for faster search operations

Kesheng Wu;E.J. Otoo;A. Shoshani.
statistical and scientific database management (2002)

193 Citations

Optimizing connected component labeling algorithms

Kesheng Wu;Ekow J. Otoo;Arie Shoshani.
SPIE Medical Imaging 2005, San Diego, California,USA, 12 17 February 2005 (2005)

184 Citations

Best Scientists Citing Kesheng Wu

Scott Klasky

Scott Klasky

Oak Ridge National Laboratory

Publications: 61

James R. Chelikowsky

James R. Chelikowsky

The University of Texas at Austin

Publications: 53

Yousef Saad

Yousef Saad

University of Minnesota

Publications: 32

Kenji Suzuki

Kenji Suzuki

Tokyo Institute of Technology

Publications: 23

Jack Dongarra

Jack Dongarra

University of Tennessee at Knoxville

Publications: 22

Manish Parashar

Manish Parashar

University of Utah

Publications: 22

Gagan Agrawal

Gagan Agrawal

Augusta University

Publications: 17

Stanimire Tomov

Stanimire Tomov

University of Tennessee at Knoxville

Publications: 16

Nagiza F. Samatova

Nagiza F. Samatova

North Carolina State University

Publications: 14

Robert Ross

Robert Ross

Argonne National Laboratory

Publications: 14

Leeor Kronik

Leeor Kronik

Weizmann Institute of Science

Publications: 13

Michael F. Wehner

Michael F. Wehner

Lawrence Berkeley National Laboratory

Publications: 12

Kwan-Liu Ma

Kwan-Liu Ma

University of California, Davis

Publications: 12

Akihiro Morita

Akihiro Morita

Tohoku University

Publications: 12

Tahsin Kurc

Tahsin Kurc

Stony Brook University

Publications: 11

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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