John Mark Agosta
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Sociology and Political Science
- Signal Processing
- Co-authors
- Rob EnnalsBeth TrushkowskyJaideep ChandrashekarEve M. SchoolerDenver DashBarbara RosarioCarl LivadasBranislav Kveton
- Topics
- Bayesian Modeling and Causal Inference (3 papers)Maritime Navigation and Safety (3 papers)Network Security and Intrusion Detection (3 papers)
- Journals
- British Journal of Educational TechnologyarXiv (Cornell University)OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
John Mark Agosta
12 papers receiving 202 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 134
- Computer Networks and Communications 89
- Information Systems 67
- Sociology and Political Science 55
- Signal Processing 40
Countries citing papers authored by John Mark Agosta
This map shows the geographic impact of John Mark Agosta'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 Mark Agosta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Mark Agosta more than expected).
Fields of papers citing papers by John Mark Agosta
This network shows the impact of papers produced by John Mark Agosta. 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 Mark Agosta. The network helps show where John Mark Agosta may publish in the future.
Co-authorship network of co-authors of John Mark Agosta
This figure shows the co-authorship network connecting the top 25 collaborators of John Mark Agosta. A scholar is included among the top collaborators of John Mark Agosta 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 Mark Agosta. John Mark Agosta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 31 | |
| 5 | 73 | |
| 6 | An adaptive anomaly detector for worm detection | 22 |
| 7 | When gossip is good: distributed probabilistic inference for detection of slow network intrusions | 42 |
| 8 | 22 | |
| 9 | 13 | |
| 10 | Spill response system configuration study. Final report | 1 |
| 11 | 1 | |
| 12 | Probabilistic recognition networks: an application of influence diagrams to visual recognition | 2 |
About John Mark Agosta
John Mark Agosta is a scholar working on Communication, Artificial Intelligence and Ocean Engineering, having authored 12 papers that have together received 215 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Maritime Navigation and Safety (3 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Artificial Intelligence (134 citations), Computer Networks and Communications (89 citations) and Signal Processing (40 citations). John Mark Agosta has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Rob Ennals, Beth Trushkowsky, Jaideep Chandrashekar, Eve M. Schooler, Denver Dash, Barbara Rosario, Carl Livadas, Branislav Kveton, Abraham Bachrach and Alexander Newman. Their work appears in journals such as British Journal of Educational Technology, arXiv (Cornell University) and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
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.