John Mullane
Impact in
- Aerospace Engineering top 5%
- Robotics and Sensor-Based Localization
- Artificial Intelligence top 5%
- Target Tracking and Data Fusion in Sensor Networks
- Gaussian Processes and Bayesian Inference
Papers in
-
- Target Tracking and Data Fusion in Sensor Networks 14
-
- Robotics and Sensor-Based Localization 11
- Co-authors
- Martin Adams (15 shared papers)Ba‐Ngu Vo (11 shared papers)Ba-Tuong Vo (6 shared papers)W.S. Wijesoma (6 shared papers)Ronald Mahler (1 shared paper)Martin R. Adams (1 shared paper)Nicholas M. Patrikalakis (3 shared papers)Matthew Adams (1 shared paper)
In The Last Decade
John Mullane
18 papers receiving 553 citations
Peers
Comparison fields: 5 of 40
- Aerospace Engineering 404
- Artificial Intelligence 357
- Ocean Engineering 90
- Instrumentation 19
- Computational Mathematics 3
Countries citing papers authored by John Mullane
This map shows the geographic impact of John Mullane'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 Mullane with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Mullane more than expected).
Fields of papers citing papers by John Mullane
This network shows the impact of papers produced by John Mullane. 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 Mullane. The network helps show where John Mullane may publish in the future.
Co-authors
The 11 scholars most cited alongside John Mullane, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 222 | |
| 2 | 2014 | 63 | |
| 3 | Robotic Navigation and Mapping with Radar | 2012 | 53 |
| 4 | 2011 | 51 | |
| 5 | 2010 | 37 | |
| 6 | 2008 | 34 | |
| 7 | 2010 | 32 | |
| 8 | 2006 | 17 | |
| 9 | 2009 | 17 | |
| 10 | 2006 | 16 | |
| 11 | 2010 | 14 | |
| 12 | 2011 | 8 | |
| 13 | Random Finite Sets for Robot Mapping & SLAM: New Concepts in Autonomous Robotic Map Representations | 2011 | 5 |
| 14 | 2013 | 5 | |
| 15 | 2011 | 2 | |
| 16 | 2013 | 2 | |
| 17 | 2008 | 1 | |
| 18 | 2011 | 1 | |
| 19 | 2011 | 1 |
About John Mullane
John Mullane is a scholar working on Artificial Intelligence, Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering and Oceanography, having authored 19 papers that have together received 581 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (14 papers), Robotics and Sensor-Based Localization (11 papers), Indoor and Outdoor Localization Technologies (8 papers), Underwater Vehicles and Communication Systems (3 papers), Underwater Acoustics Research (2 papers), Remote Sensing and LiDAR Applications (2 papers), Genome Rearrangement Algorithms (1 paper) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Aerospace Engineering (404 citations), Artificial Intelligence (357 citations), Ocean Engineering (90 citations), Instrumentation (19 citations) and Computational Mathematics (3 citations). John Mullane has collaborated with scholars based in Singapore, Australia and Chile. Frequent co-authors include Martin Adams, Ba‐Ngu Vo, Ba-Tuong Vo, W.S. Wijesoma, Ronald Mahler, Martin R. Adams, Nicholas M. Patrikalakis, Matthew Adams, A.C. Rao and Franz S. Hover. Their work appears in journals such as Springer tracts in advanced robotics, IEEE Intelligent Transportation Systems Magazine, IEEE Robotics & Automation Magazine, The International Journal of Robotics Research and IEEE Sensors Journal.
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.