John Salerno
Impact in
- Artificial Intelligence top 5%
- Target Tracking and Data Fusion in Sensor Networks
- Semantic Web and Ontologies
- Anomaly Detection Techniques and Applications
- Information Systems top 5%
- Information and Cyber Security
Papers in
-
- Target Tracking and Data Fusion in Sensor Networks 6
- Bayesian Modeling and Causal Inference 5
- AI-based Problem Solving and Planning 4
- Advanced Text Analysis Techniques 3
- Anomaly Detection Techniques and Applications 3
- Co-authors
- Erik Blasch (9 shared papers)Michael Hinman (5 shared papers)Philip S. Yu (4 shared papers)Zhongfei Zhang (3 shared papers)Sun‐Ki Chai (5 shared papers)Shanchieh Jay Yang (3 shared papers)Ivan Kadar (8 shared papers)Dana Nau (2 shared papers)
- Journals
- ACM Transactions on Knowledge Discovery from Data (2 papers)Lecture notes in computer science (1 paper)International Journal of Artificial Intelligence Tools (1 paper)Medical Entomology and Zoology (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (12 papers)
- Partner nations
- United StatesGermanySweden
In The Last Decade
John Salerno
29 papers receiving 544 citations
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 326
- Information Systems 125
- Statistical and Nonlinear Physics 66
- Computer Networks and Communications 113
- Management Science and Operations Research 60
Countries citing papers authored by John Salerno
This map shows the geographic impact of John Salerno'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 John Salerno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Salerno more than expected).
Fields of papers citing papers by John Salerno
This network shows the impact of papers produced by John Salerno. 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 John Salerno. The network helps show where John Salerno may publish in the future.
Co-authors
The 25 scholars most cited alongside John Salerno, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 73 | |
| 2 | 2005 | 72 | |
| 3 | 2005 | 60 | |
| 4 | 2003 | 60 | |
| 5 | 2008 | 58 | |
| 6 | 2006 | 58 | |
| 7 | Resource Management Coordination with Level 2/3 Fusion Issues and Challenges | 2008 | 52 |
| 8 | 2006 | 35 | |
| 9 | 2005 | 26 | |
| 10 | 2011 | 22 | |
| 11 | 2007 | 13 | |
| 12 | 2003 | 12 | |
| 13 | 2013 | 11 | |
| 14 | 2007 | 6 | |
| 15 | Advances in Social Computing | 2011 | 6 |
| 16 | 2007 | 6 | |
| 17 | 2009 | 5 | |
| 18 | 2017 | 5 | |
| 19 | 2003 | 4 | |
| 20 | 2010 | 3 |
About John Salerno
John Salerno is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Social Psychology and Signal Processing, having authored 31 papers that have together received 604 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (6 papers), Bayesian Modeling and Causal Inference (5 papers), AI-based Problem Solving and Planning (4 papers), Human-Automation Interaction and Safety (4 papers), Advanced Text Analysis Techniques (3 papers), Anomaly Detection Techniques and Applications (3 papers), Data Management and Algorithms (2 papers) and Healthcare Technology and Patient Monitoring (2 papers). The work is most often cited by research in Artificial Intelligence (326 citations), Information Systems (125 citations), Statistical and Nonlinear Physics (66 citations), Computer Networks and Communications (113 citations) and Management Science and Operations Research (60 citations). John Salerno has collaborated with scholars based in United States, Germany and Sweden. Frequent co-authors include Erik Blasch, Michael Hinman, Philip S. Yu, Zhongfei Zhang, Sun‐Ki Chai, Shanchieh Jay Yang, Ivan Kadar, Dana Nau, Subrata Das and Mieczyslaw M. Kokar. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, Lecture notes in computer science, International Journal of Artificial Intelligence Tools, Medical Entomology and Zoology and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.