R.M. Fujimoto

3.1k total citations · 1 hit paper
53 papers, 2.1k citations indexed

About

R.M. Fujimoto is a scholar working on Computer Networks and Communications, Management Science and Operations Research and Hardware and Architecture. According to data from OpenAlex, R.M. Fujimoto has authored 53 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Computer Networks and Communications, 46 papers in Management Science and Operations Research and 8 papers in Hardware and Architecture. Recurrent topics in R.M. Fujimoto's work include Simulation Techniques and Applications (46 papers), Distributed and Parallel Computing Systems (30 papers) and Advanced Data Storage Technologies (13 papers). R.M. Fujimoto is often cited by papers focused on Simulation Techniques and Applications (46 papers), Distributed and Parallel Computing Systems (30 papers) and Advanced Data Storage Technologies (13 papers). R.M. Fujimoto collaborates with scholars based in United States, Taiwan and Italy. R.M. Fujimoto's co-authors include George F. Riley, Mostafa Ammar, Kalyan S. Perumalla, Christopher D. Carothers, Hao Wu, Hao Wu, Michael Hunter, Judith Dahmann, Richard Weatherly and Yi‐Bing Lin and has published in prestigious journals such as IEEE Transactions on Software Engineering, IEEE Transactions on Vehicular Technology and IEEE Transactions on Computers.

In The Last Decade

R.M. Fujimoto

51 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Parallel and distributed simulation systems

2002 845 citations R.M. Fujimoto Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
R.M. Fujimoto United States	20	1.5k	1.4k	319	295	212	53	2.1k
George F. Riley United States	23	480 0.3×	1.7k 1.2×	240 0.8×	84 0.3×	63 0.3×	93	1.9k
Rajive Bagrodia United States	33	1.0k 0.7×	5.8k 4.0×	674 2.1×	123 0.4×	151 0.7×	181	6.4k
Sandeep Neema United States	22	141 0.1×	480 0.3×	428 1.3×	77 0.3×	199 0.9×	99	1.4k
Libero Nigro Italy	16	193 0.1×	408 0.3×	220 0.7×	141 0.5×	301 1.4×	142	931
Yong Meng Teo Singapore	18	252 0.2×	763 0.5×	183 0.6×	81 0.3×	46 0.2×	105	1.2k
G. Franceschinis Italy	17	181 0.1×	658 0.5×	272 0.9×	509 1.7×	1.1k 5.2×	76	2.0k
Gianfranco Ciardo United States	25	180 0.1×	795 0.6×	386 1.2×	523 1.8×	1.1k 5.0×	99	2.1k
Alfredo Garro Italy	19	327 0.2×	282 0.2×	41 0.1×	155 0.5×	201 0.9×	103	1.0k
Satish K. Tripathi United States	28	198 0.1×	3.4k 2.4×	490 1.5×	265 0.9×	172 0.8×	175	3.9k
Robert Y. Al-Jaar United States	5	88 0.1×	1.1k 0.8×	231 0.7×	191 0.6×	234 1.1×	10	1.7k

Countries citing papers authored by R.M. Fujimoto

Since Specialization

Citations

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

Fields of papers citing papers by R.M. Fujimoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R.M. Fujimoto. 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 R.M. Fujimoto. The network helps show where R.M. Fujimoto may publish in the future.

Co-authorship network of co-authors of R.M. Fujimoto

This figure shows the co-authorship network connecting the top 25 collaborators of R.M. Fujimoto. A scholar is included among the top collaborators of R.M. Fujimoto 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 R.M. Fujimoto. R.M. Fujimoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Wu, Hao, R.M. Fujimoto, George F. Riley, & Michael Hunter. (2009). Spatial Propagation of Information in Vehicular Networks. IEEE Transactions on Vehicular Technology. 58(1). 420–431. 82 indexed citations

2.

Lobb, Collin J., Zenas C. Chao, R.M. Fujimoto, & Steve M. Potter. (2005). Parallel Event-Driven Neural Network Simulations Using the Hodgkin-Huxley Neuron Model. 16–25. 19 indexed citations

3.

Fujimoto, R.M., et al.. (2005). Background Execution of Time Warp Programs. 18. 12–19. 15 indexed citations

4.

Fujimoto, R.M., et al.. (2004). IDSim: an extensible framework for Interoperable Distributed Simulation. 532–539. 12 indexed citations

5.

Fujimoto, R.M.. (2004). Distributed simulation systems. 124–134. 34 indexed citations

6.

Loper, Margaret L. & R.M. Fujimoto. (2004). A case study in exploiting temporal uncertainty in parallel simulations. Proceedings of the International Conference on Parallel Processing. 161–168. 9 indexed citations

7.

Santoro, Andrea & R.M. Fujimoto. (2004). Off-Loading Data Distribution Management to Network Processors in HLA-Based Distributed Simulations. 1. 12–19. 6 indexed citations

8.

Fujimoto, R.M., et al.. (2004). Large-scale network simulation: how big? how fast?. 116–123. 137 indexed citations

9.

Carothers, Christopher D., Kalyan S. Perumalla, & R.M. Fujimoto. (2003). Efficient optimistic parallel simulations using reverse computation. 126–135. 15 indexed citations

10.

Fujimoto, R.M., et al.. (2002). Distributed simulation of large-scale PCS networks. 2–6. 34 indexed citations

11.

Carothers, Christopher D., R.M. Fujimoto, & Yi‐Bing Lin. (2002). A case study in simulating PCS networks using time warp. 87–94. 26 indexed citations

12.

Fujimoto, R.M.. (2002). Parallel and distributed simulation systems. Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304). 147–157. 845 indexed citations breakdown →

13.

Fujimoto, R.M., et al.. (1998). Synchronized data distribution management in distributed simulations. 28(1). 108–115. 39 indexed citations

14.

Fujimoto, R.M., et al.. (1998). Synchronized data distribution management in distributed simulations. ACM SIGSIM Simulation Digest. 28(1). 108–115. 7 indexed citations

15.

Dahmann, Judith, R.M. Fujimoto, & Richard Weatherly. (1997). The Department Of Defense High Level. Winter Simulation Conference. 142–149. 53 indexed citations

16.

Madisetti, Vijay K., et al.. (1993). The MIMDIX Environment for Parallel Simulation. Journal of Parallel and Distributed Computing. 18(4). 473–483. 32 indexed citations

17.

Akyildiz, Ian F., Liang Chen, Samir R. Das, R.M. Fujimoto, & Richard F. Serfozo. (1993). The Effect of Memory Capacity on Time Warp Performance. Journal of Parallel and Distributed Computing. 18(4). 411–422. 21 indexed citations

18.

Fujimoto, R.M., et al.. (1992). Design and evaluation of the rollback chip: special purpose hardware for Time Warp. IEEE Transactions on Computers. 41(1). 68–82. 73 indexed citations

19.

Fujimoto, R.M.. (1989). The virtual time machine. 199–208. 49 indexed citations

20.

Fujimoto, R.M., et al.. (1988). Design and performance of special purpose hardware for time warp. ACM SIGARCH Computer Architecture News. 16(2). 401–409. 17 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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