What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Software
Xiaofeng Wang spends much of his time researching Artificial intelligence, Pattern recognition, Agile software development, Process management and Hypersphere.
His work on Artificial neural network, Overfitting and Learning models as part of general Artificial intelligence research is frequently linked to Generalization, thereby connecting diverse disciplines of science.
His Agile software development study combines topics in areas such as Knowledge management, Software development, Systems engineering and Agile Unified Process.
His work deals with themes such as Agile practices, Software, Key, Process and Conceptualization, which intersect with Process management.
His studies deal with areas such as Classifier, Recognition system, Computer vision, Leaf recognition and Classification methods as well as Hypersphere.
His research integrates issues of Classification rate, Binary image, Feature and Feature data in his study of Classifier.
His most cited work include:
- Leaf shape based plant species recognition (300 citations)
- Coevolving Systems and the Organization of Agile Software Development (203 citations)
- 'Lots Done, More To Do': the Current State of Agile Systems Development Research (197 citations)
What are the main themes of his work throughout his whole career to date?
Xiaofeng Wang mainly focuses on Software, Agile software development, Knowledge management, Software development and Software engineering.
His Software research incorporates themes from Process and Data science.
His studies in Agile software development integrate themes in fields like Lean software development, Process management, Empirical process, Agile usability engineering and Agile Unified Process.
Lean software development is the subject of his research, which falls under Software development process.
His Agile usability engineering study frequently links to other fields, such as Extreme programming practices.
Xiaofeng Wang works on Software development which deals in particular with Personal software process.
He most often published in these fields:
- Software (17.25%)
- Agile software development (16.71%)
- Knowledge management (11.59%)
What were the highlights of his more recent work (between 2017-2021)?
- Software (17.25%)
- Software engineering (10.24%)
- Data science (4.31%)
In recent papers he was focusing on the following fields of study:
Software, Software engineering, Data science, Chemical engineering and Composite material are his primary areas of study.
The Software study combines topics in areas such as Engineering management, Knowledge management, Process and Set.
His research on Software engineering focuses in particular on Agile software development.
His study in Agile software development is interdisciplinary in nature, drawing from both Requirements engineering, Dependability, Software development and Life-critical system.
His research in Data science intersects with topics in Business metrics and Software metric.
His work on Graphene as part of his general Chemical engineering study is frequently connected to Anode, thereby bridging the divide between different branches of science.
Between 2017 and 2021, his most popular works were:
- Novel Materials for 3D Printing by Photopolymerization (107 citations)
- Commandersong: a systematic approach for practical adversarial voice recognition (85 citations)
- Understanding Membership Inferences on Well-Generalized Learning Models (84 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Software
His primary scientific interests are in Chemical engineering, Ceramic, Software, Composite material and Anode.
His Ceramic study integrates concerns from other disciplines, such as Compressive strength and Polymer.
His biological study spans a wide range of topics, including Data science, Process and Set.
His Data science research is multidisciplinary, relying on both Quality, Agile software development, Design science research and User story.
His Process research integrates issues from Quality management, Lead time, Process management and Product innovation.
His Inkwell and Roll-to-roll processing study in the realm of Composite material connects with subjects such as Scale and Supercapacitor.
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