Adam M. Johansen
- Artificial Intelligence top 5%
- Statistics and Probability top 2%
- Molecular Biology
- Control and Systems Engineering
- Finance top 10%
- Co-authors
- Randal DoucJohn A. D. AstonYan ZhouXavier DidelotDaniel J. LawsonRichard G. EverittFrancisco J. RubioAnthony Lee
- Topics
- Bayesian Methods and Mixture Models (18 papers)Target Tracking and Data Fusion in Sensor Networks (15 papers)Gaussian Processes and Bayesian Inference (10 papers)
- Journals
- Proceedings of the National Academy of SciencesSHILAP Revista de lepidopterologíaJournal of the American Statistical Association
- Partner nations
- United KingdomCanadaFrance
In The Last Decade
Adam M. Johansen
42 papers receiving 684 citations
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 346
- Statistics and Probability 212
- Molecular Biology 80
- Control and Systems Engineering 57
- Finance 51
Countries citing papers authored by Adam M. Johansen
This map shows the geographic impact of Adam M. Johansen'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 Adam M. Johansen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam M. Johansen more than expected).
Fields of papers citing papers by Adam M. Johansen
This network shows the impact of papers produced by Adam M. Johansen. 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 Adam M. Johansen. The network helps show where Adam M. Johansen may publish in the future.
Co-authorship network of co-authors of Adam M. Johansen
This figure shows the co-authorship network connecting the top 25 collaborators of Adam M. Johansen. A scholar is included among the top collaborators of Adam M. Johansen 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 Adam M. Johansen. Adam M. Johansen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | A particle method for solving Fredholm equations of the first kind | 1 |
| 6 | Generalised Bayesian Filtering via Sequential Monte Carlo | 3 |
| 7 | 10 | |
| 8 | 34 | |
| 9 | 33 | |
| 10 | 8 | |
| 11 | 13 | |
| 12 | 60 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 24 | |
| 16 | 9 | |
| 17 | 61 | |
| 18 | 10 | |
| 19 | Particle Filtering and Smoothing: Fifteen years later | 7 |
| 20 | 38 |
About Adam M. Johansen
Adam M. Johansen is a scholar working on Statistics and Probability, Artificial Intelligence and Structural Biology, having authored 42 papers that have together received 709 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (18 papers), Target Tracking and Data Fusion in Sensor Networks (15 papers) and Gaussian Processes and Bayesian Inference (10 papers). The work is most often cited by research in Statistics and Probability (212 citations), Artificial Intelligence (346 citations) and Structural Biology (8 citations). Adam M. Johansen has collaborated with scholars based in United Kingdom, Canada and France. Frequent co-authors include Randal Douc, John A. D. Aston, Yan Zhou, Xavier Didelot, Daniel J. Lawson, Richard G. Everitt, Francisco J. Rubio, Anthony Lee, Manuel Davy and Ba‐Ngu Vo. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.
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.