Yun Peng
- Artificial Intelligence top 0.5%
- Information Systems top 1%
- Computer Networks and Communications top 2%
- Molecular Biology
- Management Science and Operations Research top 2%
- Co-authors
- Tim FininJames A. ReggiaYannis LabrouRong PanZhongli DingR. Scott CostAnupam JoshiLi Ding
- Topics
- Semantic Web and Ontologies (25 papers)Service-Oriented Architecture and Web Services (22 papers)Bayesian Modeling and Causal Inference (20 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Yun Peng
85 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 1.5k
- Information Systems 759
- Computer Networks and Communications 492
- Molecular Biology 281
- Management Science and Operations Research 258
Countries citing papers authored by Yun Peng
This map shows the geographic impact of Yun Peng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yun Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Peng more than expected).
Fields of papers citing papers by Yun Peng
This network shows the impact of papers produced by Yun Peng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yun Peng. The network helps show where Yun Peng may publish in the future.
Co-authorship network of co-authors of Yun Peng
This figure shows the co-authorship network connecting the top 25 collaborators of Yun Peng. A scholar is included among the top collaborators of Yun Peng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yun Peng. Yun Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 20 | |
| 5 | 15 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 20 | |
| 10 | 1 | |
| 11 | A SUPPLIER DISCOVERY FRAMEWORK FOR EFFECTIVE AND EFFICIENT CONFIGURATION OF A SUPPLY CHAIN | 4 |
| 12 | 16 | |
| 13 | A framework for Bayesian network mapping | 1 |
| 14 | A Prototype Intelligent Hybrid System for Hard Gelatin Capsule Formulation Development | 12 |
| 15 | A negotiation-based Multi-agent System for Supply Chain Management | 79 |
| 16 | The current landscape of Agent Communication Languages | 51 |
| 17 | 3 | |
| 18 | A Model of Oral Reading with Relevance to Acquired Dyslexia. | 1 |
| 19 | 3 | |
| 20 | Plausibility of diagnostic hypotheses: the nature of simplicity | 57 |
About Yun Peng
Yun Peng is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications, having authored 93 papers that have together received 2.2k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (25 papers), Service-Oriented Architecture and Web Services (22 papers) and Bayesian Modeling and Causal Inference (20 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Information Systems (759 citations) and Computer Networks and Communications (492 citations). Yun Peng has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Tim Finin, James A. Reggia, Yannis Labrou, Rong Pan, Zhongli Ding, R. Scott Cost, Anupam Joshi, Li Ding, Joel Sachs and Wiboonsak Watthayu. Their work appears in journals such as Science, IEEE Communications Magazine and IEEE Transactions on Biomedical Engineering.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.