World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
8933
World Ranking
5922
National Ranking
2673

Research.com Recognitions

  • 2010 - ACM Distinguished Member
  • 2007 - ACM Senior Member

Overview

Kesheng Wu is affiliated with the Lawrence Berkeley National Laboratory in the United States. The primary research focus is in Computer Science, with more than 100 publications in the field. Within this domain, prominent subfields include Computer Networks and Communications, Artificial Intelligence, Hardware and Architecture, Electrical and Electronic Engineering, and Surgery. The main topics of research cover a diverse range of areas such as Advanced Data Storage Technologies, Distributed and Parallel Computing Systems, Parallel Computing and Optimization Techniques, Anomaly Detection Techniques and Applications, Scientific Computing and Data Management, Network Security and Intrusion Detection, and Seismic Waves and Analysis.

The scientist has contributed to numerous papers, including:

  • ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management (2020, SoftwareX)
  • Enhancing IoT anomaly detection performance for federated learning (2022, Digital Communications and Networks)
  • Improving I/O Performance for Exascale Applications Through Online Data Layout Reorganization (2021, IEEE Transactions on Parallel and Distributed Systems)
  • The Imperial Valley Dark Fiber Project: Toward Seismic Studies Using DAS and Telecom Infrastructure for Geothermal Applications (2022, Seismological Research Letters)
  • Real-time and post-hoc compression for data from Distributed Acoustic Sensing (2022, Computers & Geosciences)

Frequent collaborators include Alex Sim, Suren Byna, Junmin Gu, Bin Dong, and Alina Lazar.

Kesheng Wu's publications have appeared often in a set of notable venues, including arXiv (Cornell University), EPJ Web of Conferences, IEEE Access, Information Sciences, and Sensors.

Additionally, Kesheng Wu has authored a book published by Springer Nature titled User-Defined Tensor Data Analysis (2021).

Recognition of professional standing is reflected in awards such as the ACM Distinguished Member (2010) and ACM Senior Member (2007).

Best Publications

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

    James R. Chelikowsky;N. Troullier;K. Wu;Y. Saad

  • Fast connected-component labeling

    Lifeng He;Yuyan Chao;Kenji Suzuki;Kesheng Wu

  • Optimizing bitmap indices with efficient compression

    Kesheng Wu;Ekow J. Otoo;Arie Shoshani

  • Thick-Restart Lanczos Method for Large Symmetric Eigenvalue Problems

    Kesheng Wu;Horst Simon

  • Optimizing two-pass connected-component labeling algorithms

    Kesheng Wu;Ekow Otoo;Kenji Suzuki

  • Optimizing connected component labeling algorithms

    Kesheng Wu;Ekow J. Otoo;Arie Shoshani

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

    Qing Liu;Jeremy Logan;Yuan Tian;Hasan Abbasi

  • On the performance of bitmap indices for high cardinality attributes

    Kesheng Wu;Ekow Otoo;Arie Shoshani

  • Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer

    Gili Rosenberg;Poya Haghnegahdar;Phil Goddard;Peter Carr

  • FastBit: interactively searching massive data

    K. Wu;S. Ahern;E. W. Bethel;E. W. Bethel;J. Chen

  • ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management

    William F. Godoy;Norbert Podhorszki;Ruonan Wang;Chuck Atkins

  • Compressing bitmap indexes for faster search operations

    Kesheng Wu;E.J. Otoo;A. Shoshani

  • Dynamic Thick Restarting of the Davidson, and the Implicitly Restarted Arnoldi Methods

    Andreas Stathopoulos;Yousef Saad;Kesheng Wu

  • Query-driven visualization of large data sets

    K. Stockinger;J. Shalf;K. Wu;E.W. Bethel

  • A Block Orthogonalization Procedure with Constant Synchronization Requirements

    Andreas Stathopoulos;Kesheng Wu

  • Ab initio molecular-dynamics simulations of Si clusters using the higher-order finite-difference-pseudopotential method

    Xiaodun Jing;N. Troullier;David Dean;N. Binggeli

  • Parallel data analysis directly on scientific file formats

    Spyros Blanas;Kesheng Wu;Surendra Byna;Bin Dong

  • Using bitmap index for interactive exploration of large datasets

    Kesheng Wu;Wendy Koegler;Jacqueline Chen;Arie Shoshani

  • Parallel index and query for large scale data analysis

    Jerry Chou;Mark Howison;Brian Austin;Kesheng Wu

  • HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets using Fast Bitmap Indices

    L. Gosink;J. Shalf;K. Stockinger;K. Wu

Frequent Co-Authors

Arie Shoshani
Arie Shoshani Lawrence Berkeley National Laboratory
Kurt Stockinger
Kurt Stockinger Zurich University of Applied Sciences
Horst D. Simon
Horst D. Simon Lawrence Berkeley National Laboratory
Scott Klasky
Scott Klasky Oak Ridge National Laboratory
Bernd Hamann
Bernd Hamann University of California, Davis
Yousef Saad
Yousef Saad University of Minnesota
Nagiza F. Samatova
Nagiza F. Samatova North Carolina State University
John Shalf
John Shalf Lawrence Berkeley National Laboratory
Hans Hagen
Hans Hagen Technical University of Kaiserslautern
Peter Nugent
Peter Nugent Lawrence Berkeley National Laboratory

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