H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 58 Citations 12,829 291 World Ranking 1824 National Ranking 171

Research.com Recognitions

Awards & Achievements

2021 - IEEE Fellow For contributions to high performance computing in processing, analysis and applications of remote sensing imagery

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Operating system
  • The Internet

Lizhe Wang mainly investigates Distributed computing, Cloud computing, Big data, Scheduling and Remote sensing. His Distributed computing research incorporates themes from Virtual machine and Genetic algorithm. His studies deal with areas such as The Internet, World Wide Web and Server as well as Cloud computing.

His biological study spans a wide range of topics, including Data-intensive computing, Sparse approximation, K-SVD and Data modeling. The various areas that Lizhe Wang examines in his Scheduling study include Schedule, Real-time computing and Resource allocation. His Remote sensing research is multidisciplinary, relying on both Wavelet transform, Artificial intelligence and Pattern recognition.

His most cited work include:

  • Cloud Computing: a Perspective Study (518 citations)
  • Scientific Cloud Computing: Early Definition and Experience (451 citations)
  • Remote sensing big data computing (280 citations)

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

His scientific interests lie mostly in Distributed computing, Artificial intelligence, Cloud computing, Remote sensing and Big data. The study incorporates disciplines such as Virtual machine, Utility computing, Grid computing, Scheduling and Workflow in addition to Distributed computing. His primary area of study in Scheduling is in the field of Fair-share scheduling.

Lizhe Wang has included themes like Machine learning, Computer vision and Pattern recognition in his Artificial intelligence study. His Cloud computing research includes elements of World Wide Web, Server, Quality of service and Data science. His research integrates issues of Feature extraction, Earth observation and Convolutional neural network in his study of Remote sensing.

He most often published in these fields:

  • Distributed computing (23.87%)
  • Artificial intelligence (20.16%)
  • Cloud computing (19.36%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (20.16%)
  • Remote sensing (16.45%)
  • Pattern recognition (11.67%)

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

His primary areas of investigation include Artificial intelligence, Remote sensing, Pattern recognition, Feature extraction and Remote sensing. Lizhe Wang has researched Artificial intelligence in several fields, including Machine learning and Computer vision. His work carried out in the field of Remote sensing brings together such families of science as Elevation, Earth observation, Convolutional neural network and Bathymetry.

The concepts of his Pattern recognition study are interwoven with issues in Image resolution and Detector. Lizhe Wang combines subjects such as Self attention, Change detection and Real-time computing with his study of Remote sensing. His Big data study combines topics in areas such as Quality of service, Cloud computing and Distributed computing.

Between 2019 and 2021, his most popular works were:

  • A Multi-Order Distributed HOSVD with Its Incremental Computing for Big Services in Cyber-Physical-Social Systems (37 citations)
  • Incremental Factorization of Big Time Series Data with Blind Factor Approximation (24 citations)
  • Orchestrating the Development Lifecycle of Machine Learning-based IoT Applications: A Taxonomy and Survey (22 citations)

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

  • Artificial intelligence
  • Operating system
  • The Internet

Lizhe Wang mostly deals with Artificial intelligence, Remote sensing, Convolutional neural network, Feature and Feature extraction. His Artificial intelligence study integrates concerns from other disciplines, such as Data modeling, Machine learning and Pattern recognition. His studies in Pattern recognition integrate themes in fields like Pixel, Spectral signature and Data set.

His research in Remote sensing intersects with topics in Classifier and Image, Generative adversarial network. As a part of the same scientific family, Lizhe Wang mostly works in the field of Feature, focusing on Discriminative model and, on occasion, Feature vector. His Feature extraction research is multidisciplinary, incorporating perspectives in Algorithm, Representation, Principal component analysis and Dimensionality reduction.

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.

Top Publications

Cloud Computing: a Perspective Study

Lizhe Wang;Gregor von Laszewski;Andrew J. Younge;Xi He.
New Generation Computing (2010)

971 Citations

Scientific Cloud Computing: Early Definition and Experience

Lizhe Wang;Jie Tao;M. Kunze;A.C. Castellanos.
high performance computing and communications (2008)

711 Citations

Power-aware scheduling of virtual machines in DVFS-enabled clusters

Gregor von Laszewski;Lizhe Wang;Andrew J. Younge;Xi He.
international conference on cluster computing (2009)

391 Citations

G-Hadoop: MapReduce across distributed data centers for data-intensive computing

Lizhe Wang;Jie Tao;Rajiv Ranjan;Holger Marten.
Future Generation Computer Systems (2013)

376 Citations

Efficient resource management for Cloud computing environments

Andrew J. Younge;Gregor von Laszewski;Lizhe Wang;Sonia Lopez-Alarcon.
international conference on green computing (2010)

350 Citations

Remote sensing big data computing

Yan Ma;Haiping Wu;Lizhe Wang;Bormin Huang.
Future Generation Computer Systems (2015)

350 Citations

Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks in a Cluster with DVFS

Lizhe Wang;Gregor von Laszewski;Jay Dayal;Fugang Wang.
grid computing (2010)

280 Citations

An overview of energy efficiency techniques in cluster computing systems

Giorgio Luigi Valentini;Walter Lassonde;Samee Ullah Khan;Nasro Min-Allah.
Cluster Computing (2013)

257 Citations

Review of performance metrics for green data centers: a taxonomy study

Lizhe Wang;Samee U. Khan.
The Journal of Supercomputing (2013)

224 Citations

Energy-aware parallel task scheduling in a cluster

Lizhe Wang;Lizhe Wang;Samee U. Khan;Dan Chen;Joanna KołOdziej.
Future Generation Computer Systems (2013)

198 Citations

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

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