His primary scientific interests are in Parallel computing, File system, Artificial intelligence, Computational science and Interface. The Parallel computing study combines topics in areas such as Distributed computing and Cluster analysis. His study in File system is interdisciplinary in nature, drawing from both Degree of parallelism, Server and Cache.
Wei-keng Liao has included themes like Social media and Identification in his Artificial intelligence study. His work carried out in the field of Computational science brings together such families of science as Supercomputer, CUDA and Parallel coordinates. His research integrates issues of NetCDF, Hierarchical Data Format, File format and Parallel processing in his study of Interface.
Wei-keng Liao spends much of his time researching Parallel computing, Scalability, Input/output, Cluster analysis and Artificial intelligence. Wei-keng Liao has researched Parallel computing in several fields, including File system and Distributed computing. His Scalability research focuses on Software and how it relates to Visualization.
As a part of the same scientific family, he mostly works in the field of Input/output, focusing on Parallel processing and, on occasion, Interface. In his research on the topic of Cluster analysis, Set and Algorithm is strongly related with Data mining. His research in Supercomputer focuses on subjects like Computational science, which are connected to Hierarchical Data Format.
Wei-keng Liao mostly deals with Artificial intelligence, Artificial neural network, Transfer of learning, Deep learning and Machine learning. His Artificial intelligence research incorporates elements of Process and Diffraction. His Deep learning research integrates issues from Degree of parallelism, Parallel computing, Scalability and Convolutional neural network.
His Scalability research focuses on subjects like Volume, which are linked to Computer network. His work in the fields of Recurrent neural network overlaps with other areas such as Materials informatics. The study incorporates disciplines such as Random forest and Data mining in addition to Layer.
Artificial intelligence, Artificial neural network, Machining, Deep learning and Set are his primary areas of study. His biological study spans a wide range of topics, including Process and Pattern recognition. His Deep learning research is multidisciplinary, relying on both Domain and Convolutional neural network.
His research in Domain intersects with topics in Layer, Data mining, Vanishing gradient problem, Knowledge integration and Random forest. He combines subjects such as Field, Identification and Big data with his study of Convolutional neural network. The concepts of his Set study are interwoven with issues in Tree and Molecular graph.
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A two-phase algorithm for fast discovery of high utility itemsets
Ying Liu;Wei-keng Liao;Alok Choudhary.
knowledge discovery and data mining (2005)
Terascale direct numerical simulations of turbulent combustion using S3D
J. H. Chen;A. Choudhary;B. De Supinski;M. Devries.
Computational Science & Discovery (2009)
A fast high utility itemsets mining algorithm
Ying Liu;Wei-keng Liao;Alok Choudhary.
Proceedings of the 1st international workshop on Utility-based data mining (2005)
Parallel netCDF: A High-Performance Scientific I/O Interface
Jianwei Li;Wei-keng Liao;Alok Choudhary;Robert Ross.
conference on high performance computing (supercomputing) (2003)
A new scalable parallel DBSCAN algorithm using the disjoint-set data structure
Md. Mostofa Ali Patwary;Diana Palsetia;Ankit Agrawal;Wei-keng Liao.
ieee international conference on high performance computing data and analytics (2012)
HACC: Simulating Sky Surveys on State-of-the-Art Supercomputing Architectures
Salman Habib;Adrian Pope;Hal Finkel;Nicholas Frontiere;Nicholas Frontiere.
New Astronomy (2016)
ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition.
Dipendra Jha;Logan Ward;Arindam Paul;Wei-Keng Liao.
Scientific Reports (2018)
Dynamically adapting file domain partitioning methods for collective I/O based on underlying parallel file system locking protocols
Wei-keng Liao;Alok Choudhary.
ieee international conference on high performance computing data and analytics (2008)
Social media evolution of the Egyptian revolution
Alok Choudhary;William Hendrix;Kathy Lee;Diana Palsetia.
Communications of The ACM (2012)
Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets
Zijiang Yang;Yuksel C. Yabansu;Reda Al-Bahrani;Wei keng Liao.
Computational Materials Science (2018)
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