What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Electrical engineering
Yang Yang mostly deals with Artificial intelligence, Social network, Machine learning, Data mining and Embedding.
In his study, Feature is strongly linked to Pattern recognition, which falls under the umbrella field of Artificial intelligence.
His Social network research integrates issues from Analytics and Patent visualisation.
The study incorporates disciplines such as Social media, Data set and Scale in addition to Machine learning.
As a member of one scientific family, he mostly works in the field of Data mining, focusing on Variety and, on occasion, Receiver operating characteristic and Class imbalance.
Yang Yang has researched Embedding in several fields, including Triadic closure, Knowledge base, Theoretical computer science and Directed graph.
His most cited work include:
- Covalent functionalization and passivation of exfoliated black phosphorus via aryl diazonium chemistry (409 citations)
- Dynamic Network Embedding by Modeling Triadic Closure Process. (163 citations)
- Inferring user demographics and social strategies in mobile social networks (159 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Social network, Theoretical computer science, Data science and Data mining.
His work on Reinforcement learning is typically connected to Link as part of general Artificial intelligence study, connecting several disciplines of science.
He has included themes like Sentence and Noisy data in his Reinforcement learning study.
His studies in Social network integrate themes in fields like Social psychology and Scale.
His study looks at the relationship between Theoretical computer science and fields such as Triadic closure, as well as how they intersect with chemical problems.
Yang Yang merges Data mining with Network structure in his study.
He most often published in these fields:
- Artificial intelligence (16.77%)
- Social network (14.19%)
- Theoretical computer science (10.97%)
What were the highlights of his more recent work (between 2018-2021)?
- Internal medicine (4.52%)
- Theoretical computer science (10.97%)
- Artificial intelligence (16.77%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Internal medicine, Theoretical computer science, Artificial intelligence, Time series and Retrospective cohort study.
His research in Theoretical computer science intersects with topics in Representation, Focus and Graph neural networks.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Replication and Set.
His Machine learning study integrates concerns from other disciplines, such as Adversarial system and Graph embedding.
He has researched Time series in several fields, including Classifier and Data mining.
His Retrospective cohort study research includes themes of Platelet, Immune system, Lymphocyte and Receiver operating characteristic.
Between 2018 and 2021, his most popular works were:
- A network's gender composition and communication pattern predict women's leadership success. (37 citations)
- Ocular Dectection of SARS-CoV-2 in 114 Cases of COVID-19 Pneumonia in Wuhan, China: An Observational Study (20 citations)
- Learning Fair Representations via an Adversarial Framework (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Electrical engineering
His primary scientific interests are in Machine learning, Artificial intelligence, 2019-20 coronavirus outbreak, Severe acute respiratory syndrome coronavirus 2 and Virology.
His Machine learning research is multidisciplinary, incorporating perspectives in Graph embedding and Credit risk.
Particularly relevant to Adversarial system is his body of work in Artificial intelligence.
Yang Yang has included themes like Observational study, Disease transmission and Pneumonia in his 2019-20 coronavirus outbreak study.
His research integrates issues of Viral transmission and Betacoronavirus in his study of Severe acute respiratory syndrome coronavirus 2.
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