John Salerno

1.1k total citations
31 papers, 604 citations indexed

About

John Salerno is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, John Salerno has authored 31 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Information Systems and 5 papers in Computer Networks and Communications. Recurrent topics in John Salerno's work include Target Tracking and Data Fusion in Sensor Networks (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Human-Automation Interaction and Safety (4 papers). John Salerno is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Human-Automation Interaction and Safety (4 papers). John Salerno collaborates with scholars based in United States, Germany and Sweden. John Salerno's 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 and has published in prestigious journals such as Lecture notes in computer science, ACM Transactions on Knowledge Discovery from Data and International Journal of Artificial Intelligence Tools.

In The Last Decade

John Salerno

29 papers receiving 544 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John Salerno United States 12 326 125 113 81 75 31 604
Eugene Santos United States 17 620 1.9× 146 1.2× 170 1.5× 80 1.0× 34 0.5× 136 1.0k
Pontus Svenson Sweden 11 184 0.6× 52 0.4× 81 0.7× 87 1.1× 24 0.3× 52 461
Nong Ye United States 13 177 0.5× 132 1.1× 158 1.4× 40 0.5× 20 0.3× 49 604
Piotr J. Gmytrasiewicz United States 18 749 2.3× 41 0.3× 167 1.5× 123 1.5× 70 0.9× 67 1.1k
Jiaxing Shang China 16 283 0.9× 152 1.2× 175 1.5× 46 0.6× 19 0.3× 68 818
Mohamed Dekhil United States 9 316 1.0× 158 1.3× 55 0.5× 58 0.7× 25 0.3× 35 491
Shah Khalid Khan Australia 15 104 0.3× 122 1.0× 77 0.7× 46 0.6× 99 1.3× 41 657
Arunesh Sinha United States 13 294 0.9× 126 1.0× 155 1.4× 78 1.0× 9 0.1× 49 625
Ruocheng Guo United States 18 485 1.5× 197 1.6× 43 0.4× 78 1.0× 34 0.5× 52 781
Xiangyu Song China 11 538 1.7× 142 1.1× 60 0.5× 56 0.7× 11 0.1× 28 746

Countries citing papers authored by John Salerno

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of John Salerno

This figure shows the co-authorship network connecting the top 25 collaborators of John Salerno. A scholar is included among the top collaborators of John Salerno 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 John Salerno. John Salerno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
McDonald, Nathan, et al.. (2023). Integrating complex valued hyperdimensional computing with modular artificial neural networks. 20–20. 2 indexed citations
2.
Salerno, John, Shanchieh Jay Yang, Dana Nau, & Sun‐Ki Chai. (2011). Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction. 3 indexed citations
3.
Chai, Sun‐Ki, John Salerno, & Patricia L. Mabry. (2011). Advances in Social Computing. 6 indexed citations
4.
Salerno, John. (2011). Social computing, behavioral-cultural modeling and prediction : 4th International Conference, SBP 2011, College Park, MD, USA, March 29-31, 2011 : proceedings. Medical Entomology and Zoology. 2 indexed citations
5.
Salerno, John, et al.. (2011). The national operational environment model (NOEM). Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8060. 80600J–80600J. 1 indexed citations
6.
7.
Chai, Sun‐Ki, John Salerno, & Patricia L. Mabry. (2010). Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction. 1 indexed citations
8.
Agarwal, Nitin, et al.. (2009). Connecting Sparsely Distributed Similar Bloggers. 11–20. 5 indexed citations
9.
Tang, Lei, Huan Liu, Jianping Zhang, Nitin Agarwal, & John Salerno. (2008). Topic taxonomy adaptation for group profiling. ACM Transactions on Knowledge Discovery from Data. 1(4). 1–28. 58 indexed citations
10.
Blasch, Erik, et al.. (2008). Resource Management Coordination with Level 2/3 Fusion Issues and Challenges. 52 indexed citations
11.
12.
Blasch, Erik, Ivan Kadar, Kenneth J. Hintz, et al.. (2007). Issues and challenges in resource management and its interaction with levels 2/3 fusion with applications to real-world problems: an annotated perspective. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6567. 656712–656712. 6 indexed citations
13.
Salerno, John. (2007). Where's level 2/3 fusion - a look back over the past 10 years. 1–4. 13 indexed citations
14.
Blasch, Erik, et al.. (2007). Resource Management and Its Interaction with Level 2/3 Fusion. 1 indexed citations
15.
16.
Blasch, Erik, Ivan Kadar, John Salerno, et al.. (2006). Issues and challenges of knowledge representation and reasoning methods in situation assessment (Level 2 Fusion). Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6235. 623510–623510. 58 indexed citations
17.
Matheus, Christopher J., Mieczyslaw M. Kokar, Kenneth Bacławski, et al.. (2005). SAWA: an assistant for higher-level fusion and situation awareness. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5813. 75–75. 72 indexed citations
18.
Salerno, John, et al.. (2005). Evaluating algorithmic techniques in supporting situation awareness. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5813. 96–96. 60 indexed citations
19.
Zhang, Zhongfei, et al.. (2003). <title>Using data mining techniques for building fusion models</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5098. 174–184. 4 indexed citations
20.
Salerno, John. (1997). An Application of a Recurrent Neural Model for Parsing Natural Language. International Journal of Artificial Intelligence Tools. 6(3). 397–419. 1 indexed citations

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.

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