Jason Williams
- Artificial Intelligence top 1%
- Computer Networks and Communications top 2%
- Aerospace Engineering top 2%
- Electrical and Electronic Engineering
- Ocean Engineering top 2%
- Co-authors
- Lennart SvenssonKarl GranströmÁngel F. García‐FernándezJohn W. FisherP.S. MaybeckYuxuan XiaRoslyn A. LauFlorian Meyer
- Topics
- Target Tracking and Data Fusion in Sensor Networks (49 papers)Distributed Sensor Networks and Detection Algorithms (22 papers)Gaussian Processes and Bayesian Inference (8 papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Jason Williams
88 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 1.3k
- Computer Networks and Communications 596
- Aerospace Engineering 577
- Electrical and Electronic Engineering 282
- Ocean Engineering 229
Countries citing papers authored by Jason Williams
This map shows the geographic impact of Jason Williams'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 Jason Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Williams more than expected).
Fields of papers citing papers by Jason Williams
This network shows the impact of papers produced by Jason Williams. 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 Jason Williams. The network helps show where Jason Williams may publish in the future.
Co-authorship network of co-authors of Jason Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Jason Williams. A scholar is included among the top collaborators of Jason Williams 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 Jason Williams. Jason Williams 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 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 19 | |
| 7 | 5 | |
| 8 | 10 | |
| 9 | 31 | |
| 10 | 41 | |
| 11 | 32 | |
| 12 | 63 | |
| 13 | Gaussian implementation of the multi-Bernoulli mixture filter | 7 |
| 14 | 187 | |
| 15 | A structured mean field approach for existence-based multiple target tracking | 8 |
| 16 | 4 | |
| 17 | 88 | |
| 18 | A Comparison of JPDA and Belief Propagation for Data Association in SSA | 2 |
| 19 | Graphical model approximations to the full Bayes random finite set filter | 3 |
| 20 | Incentive plans hold increasing lure for multis. | 1 |
About Jason Williams
Jason Williams is a scholar working on Artificial Intelligence, Computer Networks and Communications and Aerospace Engineering, having authored 92 papers that have together received 2.3k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (49 papers), Distributed Sensor Networks and Detection Algorithms (22 papers) and Gaussian Processes and Bayesian Inference (8 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computer Networks and Communications (596 citations) and Aerospace Engineering (577 citations). Jason Williams has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Lennart Svensson, Karl Granström, Ángel F. García‐Fernández, John W. Fisher, P.S. Maybeck, Yuxuan Xia, Roslyn A. Lau, Florian Meyer, René Androsch and Alicyn M. Rhoades. Their work appears in journals such as Proceedings of the IEEE, Polymer and IEEE Transactions on Signal Processing.
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.