What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- Artificial intelligence
His primary areas of study are Cloud computing, Cyber-physical system, Computer security, Wireless sensor network and Big data.
His biological study spans a wide range of topics, including Industry 4.0, Distributed computing and Vehicular ad hoc network.
His Cyber-physical system research includes elements of Key and Systems engineering.
His Computer security study combines topics in areas such as The Internet and Cloud computing security.
Jiafu Wan interconnects Quality of service and Machine to machine in the investigation of issues within Wireless sensor network.
The various areas that Jiafu Wan examines in his Big data study include Volume, Wireless network, Manufacturing engineering and Time series.
His most cited work include:
- Security of the Internet of Things: perspectives and challenges (695 citations)
- Towards smart factory for industry 4.0 (596 citations)
- Implementing smart factory of Industrie 4.0: an outlook (588 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Cloud computing, Distributed computing, Big data, Cyber-physical system and Computer network.
He has included themes like Computer security, Wireless, Wireless network and Industry 4.0 in his Cloud computing study.
As a part of the same scientific family, Jiafu Wan mostly works in the field of Computer security, focusing on Cloud computing security and, on occasion, Information privacy.
His studies in Distributed computing integrate themes in fields like Scheme, Scheduling, Edge computing and Cloud robotics.
His work carried out in the field of Big data brings together such families of science as Volume, Manufacturing engineering, The Internet, Artificial intelligence and Data science.
The concepts of his Cyber-physical system study are interwoven with issues in Control, Wireless sensor network, Software engineering and Systems engineering.
He most often published in these fields:
- Cloud computing (31.33%)
- Distributed computing (19.88%)
- Big data (18.07%)
What were the highlights of his more recent work (between 2018-2021)?
- Cloud computing (31.33%)
- Distributed computing (19.88%)
- Artificial intelligence (9.64%)
In recent papers he was focusing on the following fields of study:
His main research concerns Cloud computing, Distributed computing, Artificial intelligence, Big data and Enhanced Data Rates for GSM Evolution.
His Cloud computing research incorporates elements of Dijkstra's algorithm, Information management and NoSQL.
Jiafu Wan combines subjects such as Scheduling, Edge computing and Software deployment with his study of Distributed computing.
Jiafu Wan has researched Artificial intelligence in several fields, including Machine learning, Dropout and Pattern recognition.
His Big data research is multidisciplinary, relying on both E-commerce, Information technology, Service, Field and Data science.
His Key research is multidisciplinary, incorporating elements of Smart factory, Process, Manufacturing engineering and Cyber-physical system.
Between 2018 and 2021, his most popular works were:
- A Blockchain-Based Solution for Enhancing Security and Privacy in Smart Factory (83 citations)
- Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies (59 citations)
- A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing (49 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Operating system
- Artificial intelligence
The scientist’s investigation covers issues in Big data, Key, Smart manufacturing, Process and Distributed computing.
His research in Big data intersects with topics in Information technology, Emerging technologies and Data science.
His Key study combines topics from a wide range of disciplines, such as Control engineering, Process and Cyber-physical system.
His Smart manufacturing research incorporates themes from Data type and Volume.
His Distributed computing research is multidisciplinary, incorporating perspectives in Scheduling, Resource scheduling and Server.
His work deals with themes such as Edge computing and Job shop scheduling, which intersect with Server.
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