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Professor Jack Dongarra is a recipient of many prestigious awards, including the ACM A.M. Turing Award in 2021. His pioneering contributions to numerical linear algebra, scientific computing, and high-performance software have profound, broad, and lasting impacts on scientific studies in both conventional and emerging fields. This presentation describes Jack’s impact from different perspectives. In addition to valuable mathematical software packages and platforms he brought into existence as the building blocks of modern computing and data analysis, Jack has an extraordinarily large number of coauthors, let alone a much larger number of followers. Via his direct and broad research collaborations, Jack has kept identifying emerging challenges and making paradigm shifts. Furthermore, he has fostered a large, global high-performance computing community across various fields, generations, and cultures.

Technical Description

The impact analysis is based on a document collection, with about 59,000 published articles that directly cite Jack’s work. The collected articles are retrieved from the Semantic Scholar database as updated by April 2023. The collection is incomplete, compared to the estimated total citation number 110,000 by Google as of May 2023, due to limited data sources and access. Three networks are generated from the document collection: (1) a collaborator network, (2) a thematic content network, and (3) a geographical affiliation network. The collaboration network has about 1,660 coauthors with Jack. It is depicted in a constellation structure of 10 clusters by the similarity of publication patterns. The thematic content network is embedded in a 2D spatial space. The articles are clustered by title-abstract content into 23 broad themes. The annotation terms over each theme cluster appear most frequently in the titles and abstracts. For community detection on a network, we use the algorithm BlueRed [1, 2, 3, 4, and 5]. For the spatial embedding of a network with cluster configuration, we use a cluster-enhanced version of the algorithm SG-t-SNE. The maps at the bottom give the geographical locations of about 437 coauthor affiliations. They manifest the global impact of Jack’s contributions and collaboration. The spatial locations are determined by the combined use of Crossref and Google Maps. The data and processing codes are available upon request.

Maps & self-navigated surf-search

We present a few networks and maps generated from the retrieved data. On the thematic content map, every article is represented by a unique dot point. Clicking on the map will activate self-navigated surf-search in the following three modes.

Enjoy the surf-and-search!

Thematic Content Network

publication histogram
Statistical embedding of approximately 59,000 articles by term similarity in the tiles and abstracts, the embedding is by the algorithm and tool of SG-t-SNE. The closer two article dots are, the more the terms the articles share. A dot cluster indicates closer relationships in concepts, themes or methodologies. Click on the map to activate self-navigated surf-search.

Author Collaboration Network

10 clusters of 1,660 coauthors are listed alphabetically at the cluster peripheries, cordal edges within each cluster are coauthor links, details upon zoom in. Click on the map to activate self-navigated surf-search
collaboration network collaboration network collaboration network collaboration network collaboration network collaboration network collaboration network collaboration network collaboration network collaboration network
publication histogram
Impact Over The Years (by Google Scholar as of May 2023).


437 author affilations in red circles.

Author Information

at Duke University, NC, 27708, USA.

Sources & tools

Change log