H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 32 Citations 4,403 163 World Ranking 7197 National Ranking 684

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

The scientist’s investigation covers issues in Cloud computing, Mathematical optimization, Big data, Information technology and Metaheuristic. His studies deal with areas such as Scheduling, Scalability and Distributed computing as well as Cloud computing. The Big data study combines topics in areas such as Communications system, Data collection, Knowledge management and Medical record.

His Information technology research integrates issues from eMix, Data type, Theoretical computer science and Data science. His Metaheuristic study combines topics from a wide range of disciplines, such as Particle swarm optimization and Multi-swarm optimization. The study of Computer security is intertwined with the study of Computer network in a number of ways.

His most cited work include:

  • Software-Defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: A Survey, Some Research Issues, and Challenges (422 citations)
  • Predicting miRNA-disease association based on inductive matrix completion. (194 citations)
  • Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges (169 citations)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Machine learning, Data mining and Support vector machine. His study in Feature extraction, Deep learning, Classifier, Feature and Feature selection is carried out as part of his Artificial intelligence studies. His Feature extraction study is focused on Computer vision in general.

Convolutional neural network and Wavelet are subfields of Pattern recognition in which his conducts study. His research on Machine learning focuses in particular on Random forest. His Support vector machine course of study focuses on Cross-validation and Similarity.

He most often published in these fields:

  • Artificial intelligence (36.00%)
  • Pattern recognition (14.55%)
  • Machine learning (13.09%)

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

  • Artificial intelligence (36.00%)
  • Pattern recognition (14.55%)
  • Deep learning (7.27%)

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

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Deep learning, Machine learning and Feature extraction. Jianqiang Li has included themes like Block and Computer vision in his Artificial intelligence study. His Pattern recognition research includes elements of Data set and Sensitivity.

His Deep learning research is multidisciplinary, incorporating perspectives in Wireless, Computer security, Adversary, Spoofing attack and Identification. He interconnects Birth weight and Gestational age in the investigation of issues within Machine learning. His research in Feature extraction intersects with topics in Real-time computing and Task analysis.

Between 2019 and 2021, his most popular works were:

  • Effective large for gestational age prediction using machine learning techniques with monitoring biochemical indicators (13 citations)
  • Comparison of Different Machine Learning Approaches to Predict Small for Gestational Age Infants (13 citations)
  • iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation. (12 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Jianqiang Li mainly focuses on Artificial intelligence, Machine learning, Deep learning, Mathematical optimization and Support vector machine. His work carried out in the field of Artificial intelligence brings together such families of science as Spoofing attack and Cryptography. Jianqiang Li combines subjects such as Decoding methods and Information coding with his study of Machine learning.

His research integrates issues of Computer security, Adversary and Operating system in his study of Deep learning. His studies deal with areas such as Logistic regression, Classifier, Random forest, Tumor Cell Invasion and Feature selection as well as Support vector machine. His research investigates the link between Convolutional neural network and topics such as Cataracts that cross with problems in Feature extraction.

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

Software-Defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: A Survey, Some Research Issues, and Challenges

Qiao Yan;F. Richard Yu;Qingxiang Gong;Jianqiang Li.
IEEE Communications Surveys and Tutorials (2016)

663 Citations

A hybrid solution for privacy preserving medical data sharing in the cloud environment

Ji-Jiang Yang;Jian-Qiang Li;Yu Niu.
Future Generation Computer Systems (2015)

241 Citations

Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges

Jian-Qiang Li;F. Richard Yu;Genqiang Deng;Chengwen Luo.
IEEE Communications Surveys and Tutorials (2017)

226 Citations

Predicting miRNA-disease association based on inductive matrix completion.

Xing Chen;Lei Wang;Jia Qu;Na-Na Guan.
Bioinformatics (2018)

221 Citations

Emerging information technologies for enhanced healthcare

Ji-Jiang Yang;Jianqiang Li;Jacob Mulder;Yongcai Wang.
Computers in Industry (2015)

161 Citations

A novel multi-objective particle swarm optimization with multiple search strategies

Qiuzhen Lin;Jianqiang Li;Zhihua Du;Jianyong Chen.
European Journal of Operational Research (2015)

159 Citations

A Hybrid Path Planning Method in Unmanned Air/Ground Vehicle (UAV/UGV) Cooperative Systems

Jianqiang Li;Genqiang Deng;Chengwen Luo;Qiuzhen Lin.
IEEE Transactions on Vehicular Technology (2016)

145 Citations

MCMDA: Matrix completion for MiRNA-disease association prediction

Jian-Qiang Li;Zhi-Hao Rong;Xing Chen;Gui-Ying Yan.
Oncotarget (2017)

127 Citations

TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds

Haitao Yuan;Jing Bi;Wei Tan;MengChu Zhou.
IEEE Transactions on Systems, Man, and Cybernetics (2017)

122 Citations

Application-Aware Dynamic Fine-Grained Resource Provisioning in a Virtualized Cloud Data Center

Jing Bi;Haitao Yuan;Wei Tan;MengChu Zhou.
IEEE Transactions on Automation Science and Engineering (2017)

106 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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Top Scientists Citing Jianqiang Li

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New Jersey Institute of Technology

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Michigan State University

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Pennsylvania State University

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