What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer network
- Operating system
Shiqiang Yang mainly focuses on Artificial intelligence, Social network, Machine learning, Data mining and The Internet.
His work investigates the relationship between Artificial intelligence and topics such as Computer vision that intersect with problems in Computer graphics.
His Social network study incorporates themes from Recommender system, Ranking and Information retrieval.
His research in Machine learning intersects with topics in Node, Theoretical computer science, Hidden Markov model and Viral marketing.
Shiqiang Yang combines subjects such as Locality-sensitive hashing, Directed graph and Social graph with his study of Data mining.
His The Internet study integrates concerns from other disciplines, such as Multimedia and Peer-to-peer.
His most cited work include:
- Community preserving network embedding (387 citations)
- Mining topic-level influence in heterogeneous networks (220 citations)
- Understanding the Power of Pull-Based Streaming Protocol: Can We Do Better? (218 citations)
What are the main themes of his work throughout his whole career to date?
Shiqiang Yang spends much of his time researching Artificial intelligence, Computer vision, Computer network, The Internet and Multimedia.
His studies deal with areas such as Machine learning and Pattern recognition as well as Artificial intelligence.
Machine learning connects with themes related to Data mining in his study.
His research on Computer network frequently links to adjacent areas such as Distributed computing.
His The Internet study combines topics in areas such as Scheduling, Scalability and Software deployment.
In his work, Node is strongly intertwined with Social network, which is a subfield of Multimedia.
He most often published in these fields:
- Artificial intelligence (40.07%)
- Computer vision (22.85%)
- Computer network (16.48%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (40.07%)
- Machine learning (11.61%)
- Multimedia (11.61%)
In recent papers he was focusing on the following fields of study:
Shiqiang Yang mostly deals with Artificial intelligence, Machine learning, Multimedia, Computer network and Server.
His Artificial intelligence study frequently draws parallels with other fields, such as Computer vision.
His work in Machine learning addresses subjects such as Information cascade, which are connected to disciplines such as Node.
His Multimedia study integrates concerns from other disciplines, such as Social media, The Internet and Content delivery.
His work deals with themes such as Software deployment, Service and Social network, which intersect with The Internet.
His research in Server intersects with topics in Distributed computing and Upload.
Between 2014 and 2021, his most popular works were:
- Community preserving network embedding (387 citations)
- A Dataset for Exploring User Behaviors in VR Spherical Video Streaming (93 citations)
- Social Recommendation with Cross-Domain Transferable Knowledge (79 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Computer network
His main research concerns Artificial intelligence, Machine learning, Multimedia, Social network and Scalability.
The Artificial intelligence study combines topics in areas such as Goodness of fit and Computer vision.
His work in Machine learning tackles topics such as Information cascade which are related to areas like Node.
He combines subjects such as Cross-platform, Bridging, Content delivery, Variety and User experience design with his study of Multimedia.
Shiqiang Yang interconnects Information needs, Recommender system, Crowds and Knowledge engineering in the investigation of issues within Social network.
His Scalability research includes elements of Discrete mathematics, Denial-of-service attack, Normality and Botnet.
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