Damon McDougall

1.3k total citations · 1 hit paper
8 papers, 455 citations indexed

About

Damon McDougall is a scholar working on Hardware and Architecture, Computer Networks and Communications and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Damon McDougall has authored 8 papers receiving a total of 455 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Hardware and Architecture, 2 papers in Computer Networks and Communications and 1 paper in Cardiology and Cardiovascular Medicine. Recurrent topics in Damon McDougall's work include Parallel Computing and Optimization Techniques (3 papers), Distributed and Parallel Computing Systems (2 papers) and Statistical and numerical algorithms (1 paper). Damon McDougall is often cited by papers focused on Parallel Computing and Optimization Techniques (3 papers), Distributed and Parallel Computing Systems (2 papers) and Statistical and numerical algorithms (1 paper). Damon McDougall collaborates with scholars based in United States, United Kingdom and Mexico. Damon McDougall's co-authors include Amye Kenall, Brian A. Nosek, Karthik Ram, Kaitlin Thaney, Kara Woo, Tal Yarkoni, C. Titus Brown, Jeffrey R. Spies, Courtney K. Soderberg and Philip E. Bourne and has published in prestigious journals such as eLife, Planetary and Space Science and The International Journal of High Performance Computing Applications.

In The Last Decade

Damon McDougall

8 papers receiving 431 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.

How open science helps researchers succeed

2016 434 citations Erin C. McKiernan, Philip E. Bourne et al. eLife profile →

Peers

Damon McDougall

IS

ISM

SPU

PHEOH

AI

Kaitlin Thaney United Kingdom

Amye Kenall Germany

Sarah Piechowski Germany

Curtis Kennett United States

Peter Kraker Austria

Dalmeet Singh Chawla

Erica J. Yoon United States

Iain Hrynaszkiewicz United States

Marjorie M.K. Hlava United States

Douglas Joubert United States

Kaitlin Thaney United Kingdom

Damon McDougall

180 ×1.0

IS

181 ×1.0

ISM

174 ×1.0

SPU

47 ×1.0

PHEOH

30 ×0.9

AI

Citations per year, relative to Damon McDougall Damon McDougall (= 1×) peers Kaitlin Thaney

Countries citing papers authored by Damon McDougall

Since Specialization

Citations

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

Fields of papers citing papers by Damon McDougall

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Damon McDougall

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

All Works

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8 of 8 papers shown

1.

Chalmers, Noel, et al.. (2023). HipBone: A performance-portable graphics processing unit-accelerated C++ version of the NekBone benchmark. The International Journal of High Performance Computing Applications. 37(5). 560–577. 7 indexed citations

2.

Chalmers, Noel, Jakub Kurzak, Damon McDougall, & Paul T. Bauman. (2023). Optimizing High-Performance Linpack for Exascale Accelerated Architectures. 1–12. 6 indexed citations

3.

Malaya, Nicholas, et al.. (2017). Experiences Porting Scientific Applications to the Intel (KNL) Xeon Phi Platform. 1–8. 1 indexed citations

4.

Mattis, Steven, et al.. (2016). BET: Butler, Estep, Tavener Method v2.0.0. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

5.

McKiernan, Erin C., Philip E. Bourne, C. Titus Brown, et al.. (2016). How open science helps researchers succeed. eLife. 5. 434 indexed citations breakdown →

6.

McDougall, Damon, et al.. (2015). Uncertainty for calculating transport on Titan: A probabilistic description of bimolecular diffusion parameters. Planetary and Space Science. 117. 377–384. 2 indexed citations

7.

Mattis, Steven, et al.. (2015). BET: Butler, Estep, Tavener Method v1.0.2. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

8.

McDougall, Damon, et al.. (2011). Kalman filtering for linear wave equations with model error. arXiv (Cornell University). 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.

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