What is he best known for?
The fields of study he is best known for:
- Computer network
- Artificial intelligence
- The Internet
Computer network, Artificial intelligence, Quality of service, Wireless network and The Internet are his primary areas of study.
The concepts of his Computer network study are interwoven with issues in Wireless, Distributed computing and Communication channel.
His Artificial intelligence research integrates issues from Machine learning, Theoretical computer science, Graph and Social network.
His work deals with themes such as Network allocation vector, Wireless lan, Network address and Adaptation, which intersect with Quality of service.
His Wireless network research is multidisciplinary, incorporating elements of Mobile station, Throughput and Mobile computing.
His The Internet research incorporates themes from Service quality, Multimedia, Scalability and Resource allocation.
His most cited work include:
- Structural Deep Network Embedding (1342 citations)
- Streaming video over the Internet: approaches and directions (650 citations)
- Asymmetric Transitivity Preserving Graph Embedding (643 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Computer network, Artificial intelligence, Quality of service, Multimedia and The Internet.
His studies deal with areas such as Wireless, Wireless network, Real-time computing and Distributed computing as well as Computer network.
His Artificial intelligence study combines topics in areas such as Machine learning, Theoretical computer science, Computer vision and Pattern recognition.
His work on Resource allocation expands to the thematically related Quality of service.
His study explores the link between Multimedia and topics such as Social network that cross with problems in Social media.
His The Internet study incorporates themes from Scalability, Bandwidth and Server.
He most often published in these fields:
- Computer network (37.33%)
- Artificial intelligence (16.50%)
- Quality of service (14.54%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (16.50%)
- Theoretical computer science (6.88%)
- Graph (3.34%)
In recent papers he was focusing on the following fields of study:
Wenwu Zhu focuses on Artificial intelligence, Theoretical computer science, Graph, Deep learning and Sentence.
The Artificial intelligence study combines topics in areas such as Machine learning, Modal, Computer vision and Pattern recognition.
In his study, Adversarial system is strongly linked to Graph embedding, which falls under the umbrella field of Theoretical computer science.
He works mostly in the field of Deep learning, limiting it down to topics relating to Artificial neural network and, in certain cases, Terminal sliding mode and Control, as a part of the same area of interest.
Wenwu Zhu has researched Sentence in several fields, including Semantics, Ground and The Internet.
His studies examine the connections between The Internet and genetics, as well as such issues in Multimedia, with regards to Cloud computing.
Between 2018 and 2021, his most popular works were:
- A Survey on Network Embedding (458 citations)
- Deep Learning on Graphs: A Survey (204 citations)
- Robust Graph Convolutional Networks Against Adversarial Attacks (86 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer network
- Operating system
Wenwu Zhu mainly investigates Artificial intelligence, Theoretical computer science, Graph, Sentence and Machine learning.
His Artificial intelligence research includes elements of Node and Computer vision.
Wenwu Zhu works mostly in the field of Theoretical computer science, limiting it down to concerns involving Graph embedding and, occasionally, Adversarial system, Point, Network analysis, Focus and Network topology.
The various areas that Wenwu Zhu examines in his Sentence study include Semantics and The Internet.
He focuses mostly in the field of The Internet, narrowing it down to matters related to Thumbnail and, in some cases, Information retrieval.
In general Machine learning, his work in Recommender system is often linked to Factor, Constraint and Property linking many areas of study.
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