What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Quantum mechanics
Data mining, Complex network, Data science, Statistical physics and Unification are his primary areas of study.
His studies deal with areas such as Information science, Representation, Projection and Bipartite graph as well as Data mining.
His work deals with themes such as Centrality, Small set and Robustness, which intersect with Complex network.
His Centrality research is multidisciplinary, relying on both Spite, Message passing, State and Identification.
His Data science study combines topics from a wide range of disciplines, such as Learning to rank, Search engine, Bioinformatics, Information foraging and Social influence.
Yi-Cheng Zhang has included themes like Zipf's law, Kardar–Parisi–Zhang equation, Pairwise comparison and Renormalization in his Statistical physics study.
His most cited work include:
- Observation of Gravitational Waves from a Binary Black Hole Merger (7103 citations)
- Dynamic Scaling of Growing Interfaces (3492 citations)
- Predicting missing links via local information (960 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Recommender system, Data mining, Ranking, Complex network and Data science.
Yi-Cheng Zhang has researched Recommender system in several fields, including Probability and statistics, Popularity and Artificial intelligence.
His work in Data mining tackles topics such as Similarity which are related to areas like Metric.
His research integrates issues of Collaborative filtering, Ranking and PageRank in his study of Ranking.
His Complex network research includes themes of Complex system, Centrality, Theoretical computer science and Robustness.
His research in Data science intersects with topics in State and Identification.
He most often published in these fields:
- Recommender system (23.08%)
- Data mining (23.08%)
- Ranking (21.54%)
What were the highlights of his more recent work (between 2013-2021)?
- Complex network (17.85%)
- Data science (16.00%)
- Centrality (8.62%)
In recent papers he was focusing on the following fields of study:
Yi-Cheng Zhang mainly investigates Complex network, Data science, Centrality, Theoretical computer science and Identification.
His work on Network science as part of general Complex network research is frequently linked to Prediction methods, thereby connecting diverse disciplines of science.
The concepts of his Theoretical computer science study are interwoven with issues in Null model, Bipartite graph and Network theory.
He combines subjects such as Impact factor, Citation, State and PageRank with his study of Identification.
His Class research also works with subjects such as
- Range which connect with Data mining,
- Artificial intelligence most often made with reference to Ranking.
His study in Data mining is interdisciplinary in nature, drawing from both Similarity and Predictability.
Between 2013 and 2021, his most popular works were:
- Observation of Gravitational Waves from a Binary Black Hole Merger (7103 citations)
- Vital nodes identification in complex networks (547 citations)
- Vital nodes identification in complex networks (547 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Quantum mechanics
His primary areas of study are Complex network, Data science, Network science, Identification and Ranking.
He interconnects Data mining and Robustness in the investigation of issues within Complex network.
Data science is closely attributed to Network dynamics in his work.
His Identification study incorporates themes from Evolving networks, Learning to rank and Centrality.
His Ranking research includes elements of Network model, Artificial intelligence, Text mining, PageRank and Popularity.
His work carried out in the field of PageRank brings together such families of science as Class, Ranking and Relation.
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