What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Machine learning
His main research concerns World Wide Web, Web service, Services computing, Web modeling and WS-Policy.
His World Wide Web study combines topics in areas such as Software system, Orchestration and Data science.
His Web service research includes themes of Provisioning, Information retrieval and Service.
His study looks at the intersection of Services computing and topics like Service delivery framework with Service system.
His research in Web modeling intersects with topics in Web standards and Web development.
His biological study deals with issues like WS-I Basic Profile, which deal with fields such as Business Process Execution Language, Web engineering and Integrated services.
His most cited work include:
- Quality driven web services composition (1067 citations)
- The Self-Serv environment for Web services composition (521 citations)
- Declarative composition and peer-to-peer provisioning of dynamic Web services (399 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include World Wide Web, Web service, Artificial intelligence, Data mining and The Internet.
His research ties Service and World Wide Web together.
His is involved in several facets of Web service study, as is seen by his studies on WS-Policy, Web modeling, Service-oriented architecture and Data Web.
The various areas that Quan Z. Sheng examines in his WS-Policy study include WS-Addressing and WS-I Basic Profile.
His studies in Artificial intelligence integrate themes in fields like Machine learning, Computer vision and Pattern recognition.
His Data mining study frequently draws connections between related disciplines such as Information retrieval.
He most often published in these fields:
- World Wide Web (28.85%)
- Web service (20.73%)
- Artificial intelligence (19.66%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (19.66%)
- Machine learning (8.76%)
- Deep learning (5.13%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Deep learning, Data science and Information retrieval.
Quan Z. Sheng has researched Artificial intelligence in several fields, including Recommender system, Wearable computer and Natural language processing.
His biological study spans a wide range of topics, including Heuristic and Identification.
Quan Z. Sheng works mostly in the field of Data science, limiting it down to topics relating to Key and, in certain cases, The Internet, as a part of the same area of interest.
His research on The Internet concerns the broader World Wide Web.
His Information retrieval research is multidisciplinary, incorporating elements of Mashup, Service and Cache.
Between 2017 and 2021, his most popular works were:
- Adversarial Attacks on Deep-learning Models in Natural Language Processing: A Survey (88 citations)
- Mobile cloud computing: challenges and future research directions (58 citations)
- Nonrigid Point Set Registration With Robust Transformation Learning Under Manifold Regularization (52 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Machine learning
His primary areas of study are Artificial intelligence, Information retrieval, Data science, Machine learning and Deep learning.
His Artificial intelligence study integrates concerns from other disciplines, such as Big data, Wearable computer, Computer vision and Pattern recognition.
His work deals with themes such as Social media, Focus, Data mining and Service, which intersect with Information retrieval.
Quan Z. Sheng interconnects Field, Key and Categorization in the investigation of issues within Data science.
His Mashup study introduces a deeper knowledge of Web service.
His study with Recommender system involves better knowledge in World Wide Web.
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