Fred Daum

3.5k total citations · 2 hit papers
87 papers, 2.6k citations indexed

About

Fred Daum is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Aerospace Engineering. According to data from OpenAlex, Fred Daum has authored 87 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 15 papers in Statistical and Nonlinear Physics and 13 papers in Aerospace Engineering. Recurrent topics in Fred Daum's work include Target Tracking and Data Fusion in Sensor Networks (36 papers), Gaussian Processes and Bayesian Inference (10 papers) and Probabilistic and Robust Engineering Design (9 papers). Fred Daum is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (36 papers), Gaussian Processes and Bayesian Inference (10 papers) and Probabilistic and Robust Engineering Design (9 papers). Fred Daum collaborates with scholars based in United States and Italy. Fred Daum's co-authors include Jim Huang, Yaakov Bar‐Shalom, Jong‐Chin Huang, R.J. Fitzgerald, Peter Willett, Richard W. Osborne, Liyi Dai, Shozo Mori, Kristine L. Bell and Roy L. Streit and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Aerospace and Electronic Systems and IEEE Control Systems.

In The Last Decade

Fred Daum

84 papers receiving 2.5k citations

Hit Papers

The probabilistic data association filter 2005 2026 2012 2019 2009 2005 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fred Daum United States 22 1.8k 864 374 335 286 87 2.6k
Mark R. Morelande Australia 27 1.8k 1.0× 923 1.1× 371 1.0× 389 1.2× 631 2.2× 137 2.8k
Sanjeev Arulampalam Australia 20 2.6k 1.5× 1.2k 1.4× 639 1.7× 699 2.1× 697 2.4× 64 3.6k
Joaquı́n Mı́guez Spain 21 1.4k 0.8× 266 0.3× 417 1.1× 693 2.1× 853 3.0× 132 2.6k
Petr Tichavský Czechia 25 1.2k 0.7× 605 0.7× 381 1.0× 533 1.6× 481 1.7× 112 3.3k
Daniel E. Clark United Kingdom 30 2.6k 1.4× 1.0k 1.2× 317 0.8× 461 1.4× 943 3.3× 117 3.1k
Puneet Singla United States 21 639 0.4× 806 0.9× 461 1.2× 118 0.4× 164 0.6× 173 2.0k
Patrick Y. Hwang United States 11 1.1k 0.6× 1.8k 2.1× 681 1.8× 719 2.1× 244 0.9× 22 3.4k
Dominic Schuhmacher Switzerland 10 1.8k 1.0× 685 0.8× 253 0.7× 348 1.0× 652 2.3× 25 2.3k
J.H. Kotecha United States 14 1.6k 0.9× 446 0.5× 502 1.3× 860 2.6× 814 2.8× 29 2.7k
A. Cantoni Australia 26 1.5k 0.9× 1.0k 1.2× 405 1.1× 898 2.7× 682 2.4× 185 3.8k

Countries citing papers authored by Fred Daum

Since Specialization
Citations

This map shows the geographic impact of Fred Daum'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 Fred Daum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fred Daum more than expected).

Fields of papers citing papers by Fred Daum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fred Daum. 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 Fred Daum. The network helps show where Fred Daum may publish in the future.

Co-authorship network of co-authors of Fred Daum

This figure shows the co-authorship network connecting the top 25 collaborators of Fred Daum. A scholar is included among the top collaborators of Fred Daum 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 Fred Daum. Fred Daum 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.
Daum, Fred. (2020). A system engineering perspective on quantum radar. 958–963. 11 indexed citations
2.
Daum, Fred, et al.. (2017). Numerical experiments for Gromov’s stochastic particle flow filters. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10200. 102000J–102000J. 1 indexed citations
3.
Daum, Fred. (2016). Seven dubious methods to compute optimal Q for Bayesian stochastic particle flow. International Conference on Information Fusion. 2237–2244. 8 indexed citations
4.
Mori, Shozo, et al.. (2016). Adaptive step size approach to homotopy-based particle filtering Bayesian update. International Conference on Information Fusion. 2035–2042. 8 indexed citations
5.
Daum, Fred & Jim Huang. (2015). Renormalization group flow in k-space for nonlinear filters, Bayesian decisions and transport. International Conference on Information Fusion. 1617–1624. 5 indexed citations
6.
Streit, Roy L., et al.. (2014). Bayesian multiple target tracking, 2nd edition [Book review]. IEEE Aerospace and Electronic Systems Magazine. 29(8). 23–24. 9 indexed citations
7.
Daum, Fred & Jim Huang. (2014). How to avoid normalization of particle flow for nonlinear filters, Bayesian decisions, and transport. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9092. 90920B–90920B. 18 indexed citations
8.
Daum, Fred & Jim Huang. (2013). Particle flow for nonlinear filters, Bayesian decisions and transport. International Conference on Information Fusion. 1072–1079. 17 indexed citations
9.
Daum, Fred & Jim Huang. (2013). Zero curvature particle flow for nonlinear filters. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8745. 87450Q–87450Q. 25 indexed citations
10.
Daum, Fred & Jim Huang. (2013). Particle flow with non-zero diffusion for nonlinear filters, Bayesian decisions and transport. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8857. 88570A–88570A. 15 indexed citations
11.
Daum, Fred & Jim Huang. (2012). Particle flow and Monge-Kantorovich transport. International Conference on Information Fusion. 135–142. 17 indexed citations
12.
Daum, Fred. (2012). Tracking and data fusion: Handbook of Algorithms (Bar-Shalom, Y., et al; 2011) [Book Review]. IEEE Aerospace and Electronic Systems Magazine. 27(12). 34–35. 5 indexed citations
13.
Daum, Fred, et al.. (2011). Coulomb's law particle flow for nonlinear filters. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8137. 81370B–81370B. 25 indexed citations
14.
Daum, Fred, et al.. (2010). Exact particle flow for nonlinear filters. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7697. 769704–769704. 101 indexed citations
16.
Daum, Fred & Jim Huang. (2008). Particle flow for nonlinear filters with log-homotopy. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6969. 696918–696918. 54 indexed citations
17.
Daum, Fred & Jong‐Chin Huang. (2004). Curse of dimensionality and particle filters. 4. 4_1979–4_1993. 215 indexed citations
18.
Daum, Fred. (2002). Virtual measurements for nonlinear filters. 2. 1657–1662. 1 indexed citations
19.
Daum, Fred. (1996). Multitarget-Multisensor Tracking: Principles and Techniques [Book Review]. IEEE Aerospace and Electronic Systems Magazine. 11(2). 41–41. 8 indexed citations
20.
Daum, Fred. (1990). Bounds on performance for multiple target tracking. IEEE Transactions on Automatic Control. 35(4). 443–446. 32 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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