What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- The Internet
The scientist’s investigation covers issues in Cloud computing, Computer security, Big data, Knowledge management and Process.
The various areas that Victor Chang examines in his Cloud computing study include Software deployment, Database, Visualization, Business model and Key.
His work in the fields of Privacy software, Intrusion detection system and Data security overlaps with other areas such as Building automation.
His work carried out in the field of Big data brings together such families of science as Distributed computing, Cloud storage, Encryption, Resource and Data science.
Victor Chang works mostly in the field of Knowledge management, limiting it down to concerns involving Artifact-centric business process model and, occasionally, New business development, Business activity monitoring and Agile software development.
His studies examine the connections between Process and genetics, as well as such issues in Service, with regards to Business process, Emerging technologies and Process management.
His most cited work include:
- The role of big data in smart city (454 citations)
- Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare (328 citations)
- Cloud computing adoption framework (197 citations)
What are the main themes of his work throughout his whole career to date?
Victor Chang mainly focuses on Cloud computing, Big data, Computer security, Distributed computing and Artificial intelligence.
The various areas that he examines in his Cloud computing study include Software portability, Process, Service and Knowledge management.
His Big data study combines topics from a wide range of disciplines, such as Visualization and Data science.
His research ties World Wide Web and Data science together.
The concepts of his Distributed computing study are interwoven with issues in Resource, Quality of service, Provisioning and Server.
The study incorporates disciplines such as Machine learning and Pattern recognition in addition to Artificial intelligence.
He most often published in these fields:
- Cloud computing (36.00%)
- Big data (17.00%)
- Computer security (12.00%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (9.50%)
- Distributed computing (11.50%)
- Big data (17.00%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Distributed computing, Big data, Deep learning and Data science.
His Artificial intelligence research is multidisciplinary, relying on both Encoder, Machine learning and Pattern recognition.
His Distributed computing research is multidisciplinary, incorporating perspectives in Virtual machine, Quality of service, Cloud computing, Server and Mobile device.
His research in Cloud computing intersects with topics in Software deployment, Schedule, Resource, Scheduling and Workflow.
His work deals with themes such as Provisioning and Service, which intersect with Software deployment.
He has included themes like Ethical issues and End user in his Big data study.
Between 2019 and 2021, his most popular works were:
- An innovative neural network approach for stock market prediction (72 citations)
- A Novel Intelligent Medical Decision Support Model Based on Soft Computing and IoT (41 citations)
- HSMA_WOA: A hybrid novel Slime mould algorithm with whale optimization algorithm for tackling the image segmentation problem of chest X-ray images. (20 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- The Internet
His main research concerns Artificial intelligence, Deep learning, Computer security, Machine learning and Big data.
Victor Chang interconnects Process and Pattern recognition in the investigation of issues within Artificial intelligence.
In his research, Pyramid, Block, Feature extraction, Pyramid and Analytics is intimately related to Encoder, which falls under the overarching field of Deep learning.
Victor Chang combines subjects such as Overhead and Big data security with his study of Computer security.
His work carried out in the field of Machine learning brings together such families of science as Home automation, Classifier, Anomaly detection and Dimension.
His research investigates the connection between Big data and topics such as Knowledge extraction that intersect with problems in Process.
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