D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 41 Citations 10,529 168 World Ranking 4260 National Ranking 2142
Electronics and Electrical Engineering D-index 34 Citations 6,731 111 World Ranking 2542 National Ranking 1037

Research.com Recognitions

Awards & Achievements

2014 - IEEE Fellow For contributions to modeling of wireless ad-hoc and sensor networks


What is he best known for?

The fields of study he is best known for:

  • Computer network
  • Statistics
  • The Internet

Mingyan Liu spends much of his time researching Computer network, Wireless sensor network, Communication channel, Mathematical optimization and Real-time computing. In his research, Node, Transmission and Data collection is intimately related to Throughput, which falls under the overarching field of Computer network. His research in Wireless sensor network intersects with topics in Key distribution in wireless sensor networks, Sensor array and Embedded system.

Communication channel connects with themes related to Wireless in his study. He usually deals with Mathematical optimization and limits it to topics linked to Markov process and Fading, Regret and Markov chain. He has researched Real-time computing in several fields, including Effective method and Global Positioning System.

His most cited work include:

  • Random waypoint considered harmful (1110 citations)
  • AMRoute: ad hoc multicast routing protocol (411 citations)
  • Optimality of Myopic Sensing in Multichannel Opportunistic Access (348 citations)

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

Computer network, Mathematical optimization, Wireless sensor network, Communication channel and Wireless are his primary areas of study. The concepts of his Computer network study are interwoven with issues in Wireless network, Throughput and Distributed computing. His research integrates issues of Regret, Markov process, Markov chain and Computation in his study of Mathematical optimization.

In general Regret, his work in Multi-armed bandit is often linked to Logarithm linking many areas of study. His biological study spans a wide range of topics, including Key distribution in wireless sensor networks, Real-time computing and Cluster analysis. Cognitive radio, Fading and Diversity gain are the subjects of his Communication channel studies.

He most often published in these fields:

  • Computer network (22.30%)
  • Mathematical optimization (21.31%)
  • Wireless sensor network (17.05%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (10.16%)
  • Machine learning (6.56%)
  • Adversarial system (5.25%)

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

His scientific interests lie mostly in Artificial intelligence, Machine learning, Adversarial system, Population and Distributed algorithm. His Artificial intelligence study incorporates themes from Lidar and Computer vision. His MNIST database and Regret study, which is part of a larger body of work in Machine learning, is frequently linked to Process, bridging the gap between disciplines.

His studies deal with areas such as Rate of convergence and Mathematical optimization as well as Distributed algorithm. His Mathematical optimization study frequently links to adjacent areas such as Computation. Robustness and Computer network are frequently intertwined in his study.

Between 2016 and 2021, his most popular works were:

  • Generating Adversarial Examples with Adversarial Networks (156 citations)
  • Spatially Transformed Adversarial Examples (144 citations)
  • Generating Adversarial Examples with Adversarial Networks (123 citations)

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

  • Computer network
  • Artificial intelligence
  • Statistics

His primary areas of investigation include Adversarial system, Artificial intelligence, Machine learning, Network security and Cyber-Insurance. His Adversarial system study combines topics in areas such as Adversary, Deep neural networks, Rendering and Distance measures. Mingyan Liu studies Artificial intelligence, focusing on Reinforcement learning in particular.

His research in the fields of MNIST database overlaps with other disciplines such as Transferability. His Network security study integrates concerns from other disciplines, such as Actuarial science, Risk analysis, Profit and Externality. Mingyan Liu brings together Theoretical computer science and Context to produce work in his papers.

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.

Best Publications

Random waypoint considered harmful

J. Yoon;M. Liu;B. Noble.
international conference on computer communications (2003)

1651 Citations

AMRoute: ad hoc multicast routing protocol

Jason Xie;Rajesh R. Talpade;Anthony Mcauley;Mingyan Liu.
Mobile Networks and Applications (2002)

571 Citations

Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks

E.J. Duarte-Melo;Mingyan Liu.
global communications conference (2002)

550 Citations

Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms

Chih-fan Hsin;Mingyan Liu.
information processing in sensor networks (2004)

454 Citations

Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

Sixing Yin;Dawei Chen;Qian Zhang;Mingyan Liu.
IEEE Transactions on Mobile Computing (2012)

396 Citations

Optimality of Myopic Sensing in Multichannel Opportunistic Access

S. Ahmad;Mingyan Liu;T. Javidi;Qing Zhao.
IEEE Transactions on Information Theory (2009)

387 Citations

Revenue generation for truthful spectrum auction in dynamic spectrum access

Juncheng Jia;Qian Zhang;Qin Zhang;Mingyan Liu.
mobile ad hoc networking and computing (2009)

369 Citations

Sound mobility models

Jungkeun Yoon;Mingyan Liu;Brian Noble.
acm/ieee international conference on mobile computing and networking (2003)

363 Citations

Surface street traffic estimation

Jungkeun Yoon;Brian Noble;Mingyan Liu.
international conference on mobile systems, applications, and services (2007)

338 Citations

On the many-to-one transport capacity of a dense wireless sensor network and the compressibility of its data

Daniel Marco;Enrique J. Duarte-Melo;Mingyan Liu;David L. Neuhoff.
information processing in sensor networks (2003)

313 Citations

Best Scientists Citing Mingyan Liu

Bhaskar Krishnamachari

Bhaskar Krishnamachari

University of Southern California

Publications: 53

Jianwei Huang

Jianwei Huang

Chinese University of Hong Kong, Shenzhen

Publications: 42

Qing Zhao

Qing Zhao

Cornell University

Publications: 39

Yuguang Fang

Yuguang Fang

University of Florida

Publications: 38

Qian Zhang

Qian Zhang

Tianjin University

Publications: 35

Xiang-Yang Li

Xiang-Yang Li

University of Science and Technology of China

Publications: 33

Yunhao Liu

Yunhao Liu

Tsinghua University

Publications: 31

Qihui Wu

Qihui Wu

Nanjing University of Aeronautics and Astronautics

Publications: 30

Mario Gerla

Mario Gerla

University of California, Los Angeles

Publications: 26

Shaojie Tang

Shaojie Tang

The University of Texas at Dallas

Publications: 26

Miao Pan

Miao Pan

University of Houston

Publications: 25

Kang G. Shin

Kang G. Shin

University of Michigan–Ann Arbor

Publications: 24

Lang Tong

Lang Tong

Cornell University

Publications: 23

Yang Xiao

Yang Xiao

University of Alabama

Publications: 22

J.J. Garcia-Luna-Aceves

J.J. Garcia-Luna-Aceves

University of California, Santa Cruz

Publications: 21

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

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