2010 - ACM Distinguished Member
2007 - ACM Senior Member
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.
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.
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.
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.
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Higher-order finite-difference pseudopotential method: An application to diatomic molecules
James R. Chelikowsky;N. Troullier;K. Wu;Yousef Saad.
Physical Review B (1994)
Optimizing bitmap indices with efficient compression
Kesheng Wu;Ekow J. Otoo;Arie Shoshani.
ACM Transactions on Database Systems (2006)
Fast connected-component labeling
Lifeng He;Yuyan Chao;Kenji Suzuki;Kesheng Wu.
Pattern Recognition (2009)
Thick-Restart Lanczos Method for Large Symmetric Eigenvalue Problems
Kesheng Wu;Horst Simon.
SIAM Journal on Matrix Analysis and Applications (2000)
Optimizing two-pass connected-component labeling algorithms
Kesheng Wu;Ekow Otoo;Kenji Suzuki.
Pattern Analysis and Applications (2009)
On the performance of bitmap indices for high cardinality attributes
Kesheng Wu;Ekow Otoo;Arie Shoshani.
very large data bases (2004)
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)
FastBit: interactively searching massive data
K. Wu;S. Ahern;E. W. Bethel;E. W. Bethel;J. Chen.
Lawrence Berkeley National Laboratory (2009)
Compressing bitmap indexes for faster search operations
Kesheng Wu;E.J. Otoo;A. Shoshani.
statistical and scientific database management (2002)
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)
Profile was last updated on December 6th, 2021.
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