Roger Pearce

843 total citations
52 papers, 548 citations indexed

About

Roger Pearce is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Roger Pearce has authored 52 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 27 papers in Computer Networks and Communications and 16 papers in Information Systems. Recurrent topics in Roger Pearce's work include Graph Theory and Algorithms (26 papers), Cloud Computing and Resource Management (15 papers) and Parallel Computing and Optimization Techniques (13 papers). Roger Pearce is often cited by papers focused on Graph Theory and Algorithms (26 papers), Cloud Computing and Resource Management (15 papers) and Parallel Computing and Optimization Techniques (13 papers). Roger Pearce collaborates with scholars based in United States, Canada and Japan. Roger Pearce's co-authors include Maya Gokhale, Brian Van Essen, Nancy M. Amato, Matei Ripeanu, Sasha Ames, Ivy Peng, Barry Chen, Kofi Boakye, Hyojin Kim and Arpith C. Jacob and has published in prestigious journals such as Computer, IEEE Transactions on Parallel and Distributed Systems and AI Magazine.

In The Last Decade

Roger Pearce

49 papers receiving 533 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roger Pearce United States 13 260 245 169 146 136 52 548
Simon Kahan United States 11 344 1.3× 207 0.8× 137 0.8× 113 0.8× 159 1.2× 15 641
Wentao Han China 8 340 1.3× 160 0.7× 223 1.3× 175 1.2× 96 0.7× 23 472
Pingpeng Yuan China 11 218 0.8× 198 0.8× 303 1.8× 170 1.2× 32 0.2× 55 485
Chuntao Jiang China 9 146 0.6× 85 0.3× 182 1.1× 160 1.1× 34 0.3× 22 454
Shubho Sengupta United States 7 125 0.5× 112 0.5× 191 1.1× 153 1.0× 86 0.6× 13 447
Gabriela Jacques-Silva United States 12 93 0.4× 306 1.2× 149 0.9× 142 1.0× 54 0.4× 21 450
Jianlong Zhong Singapore 10 235 0.9× 233 1.0× 137 0.8× 183 1.3× 203 1.5× 19 426
Jinyang Li United States 12 204 0.8× 319 1.3× 152 0.9× 238 1.6× 120 0.9× 28 661
Cong Fu China 13 278 1.1× 138 0.6× 291 1.7× 122 0.8× 104 0.8× 31 618
Makoto Onizuka Japan 14 281 1.1× 335 1.4× 505 3.0× 162 1.1× 47 0.3× 65 838

Countries citing papers authored by Roger Pearce

Since Specialization
Citations

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

Fields of papers citing papers by Roger Pearce

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roger Pearce

This figure shows the co-authorship network connecting the top 25 collaborators of Roger Pearce. A scholar is included among the top collaborators of Roger Pearce 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 Roger Pearce. Roger Pearce 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.
Shi, R. S., et al.. (2025). Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs. 368–380.
2.
Peng, Ivy, et al.. (2024). UMap: An application-oriented user level memory mapping library. The International Journal of High Performance Computing Applications. 39(2). 269–282. 1 indexed citations
3.
4.
Baranzini, Sergio E., Katy Börner, John P. Morris, et al.. (2022). A biomedical open knowledge network harnesses the power of AI to understand deep human biology. AI Magazine. 43(1). 46–58. 6 indexed citations
5.
Baranzini, Sergio E., Katy Börner, John P. Morris, et al.. (2022). A Biomedical Open Knowledge Network Harnesses the Power of AI to Understand Deep Human Biology. AI Magazine. 43(1). 46–58. 6 indexed citations
6.
Gokhale, Maya, et al.. (2022). Metall: A persistent memory allocator for data-centric analytics. Parallel Computing. 111. 102905–102905. 4 indexed citations
7.
Feng, Wu-chun, et al.. (2021). Privateer: Multi-versioned Memory-mapped Data Stores for High-Performance Data Science. 1–7. 1 indexed citations
8.
Pearce, Roger, et al.. (2021). TriPoll. 1–12. 8 indexed citations
9.
Peng, Ivy, et al.. (2021). Enabling Scalable and Extensible Memory-Mapped Datastores in Userspace. IEEE Transactions on Parallel and Distributed Systems. 33(4). 866–877. 8 indexed citations
10.
Buluç, Aydın, Timothy G. Mattson, Scott McMillan, et al.. (2020). Considerations for a Distributed GraphBLAS API. 215–218. 3 indexed citations
11.
Peng, Ivy, Eric Green, Kai Wu, et al.. (2019). UMap: Enabling Application-driven Optimizations for Page Management. 71–78. 13 indexed citations
12.
Pearce, Roger, et al.. (2019). Incremental Graph Processing for On-line Analytics. 1007–1018. 8 indexed citations
13.
Pearce, Roger, et al.. (2019). You've Got Mail (YGM): Building Missing Asynchronous Communication Primitives. 221–230. 11 indexed citations
14.
Ripeanu, Matei, et al.. (2018). PruneJuice: pruning trillion-edge graphs to a precise pattern-matching solution. IEEE International Conference on High Performance Computing, Data, and Analytics. 21. 8 indexed citations
15.
16.
17.
Shantharam, Manu, et al.. (2017). Performance Evaluation of Scale-Free Graph Algorithms in Low Latency Non-volatile Memory. 1021–1028. 6 indexed citations
18.
Gokhale, Maya, et al.. (2016). Graph colouring as a challenge problem for dynamic graph processing on distributed systems. IEEE International Conference on High Performance Computing, Data, and Analytics. 30. 13 indexed citations
19.
Borth, Damian, Jaeyoung Choi, Benjamin Elizalde, et al.. (2015). Kickstarting the Commons. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–6. 6 indexed citations
20.
Essen, Brian Van, Henry H. Hsieh, Sasha Ames, Roger Pearce, & Maya Gokhale. (2013). DI-MMAP: A High Performance Memory-Map Runtime providing scalable out-of-core execution for Data-Intensive Applications. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Simon Kahan Breakdown of academic impact, for papers by Wentao Han Breakdown of academic impact, for papers by Pingpeng Yuan Breakdown of academic impact, for papers by Chuntao Jiang Breakdown of academic impact, for papers by Shubho Sengupta Breakdown of academic impact, for papers by Gabriela Jacques-Silva Breakdown of academic impact, for papers by Jianlong Zhong Breakdown of academic impact, for papers by Jinyang Li Breakdown of academic impact, for papers by Cong Fu Breakdown of academic impact, for papers by Makoto Onizuka
Rankless by CCL
2026