H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 82 Citations 21,189 635 World Ranking 385 National Ranking 15

Research.com Recognitions

Awards & Achievements

2020 - ACM Distinguished Member

2020 - ACM Senior Member

2020 - IEEE Fellow For contributions to modeling and design for cyber-physical-social systems

The Canadian Academy of Engineering

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Computer network
  • Artificial intelligence

Laurence T. Yang mainly focuses on Cloud computing, Computer network, Distributed computing, Big data and Computer security. Her work on Mobile cloud computing as part of her general Cloud computing study is frequently connected to Mobile telephony, thereby bridging the divide between different branches of science. Her Computer network research is mostly focused on the topic Wireless sensor network.

The various areas that Laurence T. Yang examines in her Distributed computing study include Energy consumption, Quality of service, Real-time computing and Scheduling, Dynamic priority scheduling. Her Big data study combines topics from a wide range of disciplines, such as Analytics, Data science and Feature learning. Her Computer security research is multidisciplinary, incorporating perspectives in The Internet, Cloud computing security, Cyber-physical system and Service.

Her most cited work include:

  • A survey on deep learning for big data (419 citations)
  • A survey on deep learning for big data (419 citations)
  • Data Mining for Internet of Things: A Survey (396 citations)

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

Her primary areas of investigation include Distributed computing, Computer network, Cloud computing, Big data and Wireless sensor network. Her work in Distributed computing tackles topics such as Scheduling which are related to areas like Real-time computing and Parallel computing. Her work deals with themes such as Wireless network and Efficient energy use, which intersect with Computer network.

Her study in Cloud computing is interdisciplinary in nature, drawing from both Computer security, Encryption, Scalability and Mobile computing. Her Big data research incorporates elements of Feature learning, Cluster analysis, Artificial intelligence and Computation. Her research combines Key distribution in wireless sensor networks and Wireless sensor network.

She most often published in these fields:

  • Distributed computing (24.39%)
  • Computer network (20.22%)
  • Cloud computing (18.01%)

What were the highlights of her more recent work (between 2017-2021)?

  • Big data (12.38%)
  • Cloud computing (18.01%)
  • Distributed computing (24.39%)

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

Her primary areas of study are Big data, Cloud computing, Distributed computing, Artificial intelligence and Computer security. Her Big data study incorporates themes from Data modeling, Cluster analysis, Feature learning, Computation and Cyber-physical system. Her Cloud computing research includes elements of Data mining, Cryptography, Enhanced Data Rates for GSM Evolution and Computer network, Encryption.

Her Computer network research focuses on Wireless sensor network in particular. Her Distributed computing study also includes fields such as

  • Scheduling and related Multi-core processor,
  • Energy consumption which connect with Quality of service. The concepts of her Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition.

Between 2017 and 2021, her most popular works were:

  • A survey on deep learning for big data (419 citations)
  • A survey on deep learning for big data (419 citations)
  • Deep Convolutional Computation Model for Feature Learning on Big Data in Internet of Things (105 citations)

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

  • Operating system
  • Computer network
  • Artificial intelligence

Her primary areas of study are Big data, Cloud computing, Distributed computing, Cluster analysis and Data mining. Her Big data research is multidisciplinary, relying on both Data modeling, Scalability, Feature learning, Artificial intelligence and Computation. Her Feature learning course of study focuses on Deep learning and Data science, Informatics, Variety and Wireless sensor network.

Her research in Cloud computing tackles topics such as Computer security which are related to areas like Industrial Internet. The Distributed computing study combines topics in areas such as Data processing, Service, Tree, Data structure and Cyber-physical system. Her Cluster analysis study deals with Algorithm intersecting with Decomposition.

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

Data Mining for Internet of Things: A Survey

Chun-Wei Tsai;Chin-Feng Lai;Ming-Chao Chiang;Laurence T. Yang.
IEEE Communications Surveys and Tutorials (2014)

613 Citations

A survey on deep learning for big data

Qingchen Zhang;Qingchen Zhang;Laurence T. Yang;Laurence T. Yang;Zhikui Chen;Peng Li.
Information Fusion (2018)

585 Citations

The Internet of Things: From RFID to the Next-Generation Pervasive Networked Systems

Lu Yan;Yan Zhang;Laurence T. Yang;Huansheng Ning.
(2008)

365 Citations

Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions

Jiafu Wan;Daqiang Zhang;Shengjie Zhao;Laurence T. Yang.
IEEE Communications Magazine (2014)

360 Citations

A 22nm SoC platform technology featuring 3-D tri-gate and high-k/metal gate, optimized for ultra low power, high performance and high density SoC applications

C.-H. Jan;U. Bhattacharya;R. Brain;S.-J. Choi.
international electron devices meeting (2012)

326 Citations

CloudThings: A common architecture for integrating the Internet of Things with Cloud Computing

Jiehan Zhou;Teemu Leppanen;Erkki Harjula;Mika Ylianttila.
computer supported cooperative work in design (2013)

285 Citations

A Scalable Two-Phase Top-Down Specialization Approach for Data Anonymization Using MapReduce on Cloud

Xuyun Zhang;Laurence T. Yang;Chang Liu;Jinjun Chen.
IEEE Transactions on Parallel and Distributed Systems (2014)

283 Citations

Proceedings of the 5th international symposium on Parallel and Distributed Processing and Applications

Ivan Stojmenovic;Ruppa K. Thulasiram;Laurence T. Yang;Weijia Jia.
international symposium on parallel and distributed processing and applications (2007)

281 Citations

Cyberentity Security in the Internet of Things

Huansheng Ning;Hong Liu;L. T. Yang.
IEEE Computer (2013)

253 Citations

Trace analysis and mining for smart cities: issues, methods, and applications

Gang Pan;Guande Qi;Wangsheng Zhang;Shijian Li.
IEEE Communications Magazine (2013)

241 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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