What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Machine learning
Zhiqi Shen mainly focuses on Artificial intelligence, Machine learning, Multi-agent system, Artificial neural network and Crowdsourcing.
His Artificial intelligence study frequently intersects with other fields, such as Ethical decision.
In the subject of general Machine learning, his work in Transfer of learning and Decision tree is often linked to Activities of daily living and Exercise prescription, thereby combining diverse domains of study.
His research integrates issues of Intelligent agent and Knowledge management in his study of Multi-agent system.
The Knowledge management study combines topics in areas such as Trust management and Software engineering.
His research in Crowdsourcing intersects with topics in Decision support system and Operations research.
His most cited work include:
- A Survey of Trust and Reputation Management Systems in Wireless Communications (229 citations)
- Balanced Distribution Adaptation for Transfer Learning (170 citations)
- A Survey of Multi-Agent Trust Management Systems (152 citations)
What are the main themes of his work throughout his whole career to date?
Zhiqi Shen focuses on Artificial intelligence, Knowledge management, Multi-agent system, Human–computer interaction and Machine learning.
In his research, Operations research and Quality is intimately related to Crowdsourcing, which falls under the overarching field of Knowledge management.
His Multi-agent system study combines topics from a wide range of disciplines, such as Intelligent agent, Goal orientation and Software agent.
Within one scientific family, Zhiqi Shen focuses on topics pertaining to Multimedia under Human–computer interaction, and may sometimes address concerns connected to Educational technology, Instructional simulation and Virtual reality.
Zhiqi Shen studies Transfer of learning, a branch of Machine learning.
His Fuzzy cognitive map course of study focuses on Inference and Knowledge representation and reasoning.
He most often published in these fields:
- Artificial intelligence (27.11%)
- Knowledge management (16.89%)
- Multi-agent system (14.67%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (27.11%)
- Machine learning (13.33%)
- Knowledge management (16.89%)
In recent papers he was focusing on the following fields of study:
Zhiqi Shen mostly deals with Artificial intelligence, Machine learning, Knowledge management, Human–computer interaction and Process.
His work on Deep learning and Taxonomy as part of general Artificial intelligence study is frequently linked to Research community, Field and Corporate governance, therefore connecting diverse disciplines of science.
His study on Transfer of learning and Leverage is often connected to Noise, Marginal distribution and Conditional probability distribution as part of broader study in Machine learning.
The study incorporates disciplines such as Crowdsourcing, Multi-agent system, Task and Software engineering in addition to Knowledge management.
He has researched Human–computer interaction in several fields, including User interface, Goal orientation, Cluster analysis and Personalization.
His Process research incorporates themes from Stability, Semantics and Mathematical optimization.
Between 2015 and 2021, his most popular works were:
- Balanced Distribution Adaptation for Transfer Learning (170 citations)
- Blockchain and IoT based Food Traceability for Smart Agriculture (61 citations)
- Using Blockchain Technology to Build Trust in Sharing LoRaWAN IoT (51 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Machine learning
His main research concerns Artificial intelligence, Knowledge management, Crowdsourcing, Task and Computer security.
His research investigates the link between Artificial intelligence and topics such as Machine learning that cross with problems in Data modeling.
His Knowledge management research integrates issues from Decision support system and Software development.
His study in Crowdsourcing is interdisciplinary in nature, drawing from both Payment and Operations research.
His Computer security research includes themes of Edge computing and Network operations center.
His work deals with themes such as Cellular network and Blockchain, which intersect with Network operations center.
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.
