Matthew Ward

729 total citations
22 papers, 429 citations indexed

About

Matthew Ward is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Matthew Ward has authored 22 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 9 papers in Signal Processing and 9 papers in Artificial Intelligence. Recurrent topics in Matthew Ward's work include Data Visualization and Analytics (11 papers), Data Management and Algorithms (6 papers) and Image Retrieval and Classification Techniques (4 papers). Matthew Ward is often cited by papers focused on Data Visualization and Analytics (11 papers), Data Management and Algorithms (6 papers) and Image Retrieval and Classification Techniques (4 papers). Matthew Ward collaborates with scholars based in United States, Norway and Canada. Matthew Ward's co-authors include Jing Yang, Eamonn Maguire, Min Chen, Rita Borgo, Helwig Hauser, Robert S. Laramee, David Chung, Johannes Kehrer, Elke A. Rundensteiner and Philip Waggoner and has published in prestigious journals such as The Journal of Politics, IEEE Transactions on Visualization and Computer Graphics and IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control.

In The Last Decade

Matthew Ward

19 papers receiving 405 citations

Peers

Countries citing papers authored by Matthew Ward

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Ward

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Ward

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Ward. A scholar is included among the top collaborators of Matthew Ward 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 Matthew Ward. Matthew Ward 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

#	Title	Journal	Authors	Indexed citations
1	The dimensions of judicial legitimacy: assessing the impact of Latino representation	Politics Groups and Identities	Jason P. Casellas, Matthew Ward et al.	0
2	The Impact of Racial Representation on Judicial Legitimacy: White Reactions to Latinos on the Bench	Political Research Quarterly	Jason P. Casellas, Matthew Ward et al.	9
3	Trust in Public Policy Algorithms	The Journal of Politics	Ryan Kennedy, Philip Waggoner et al.	19
4	The Impact of Input Rules and Ballot Options on Voting Error: An Experimental Analysis	Politics and Governance	Matthew Ward et al.	10
5	Trust in Public Policy Algorithms	SSRN Electronic Journal	Ryan Kennedy, Philip Waggoner et al.	8
6	Mining and linking patterns across live data streams and stream archives	Proceedings of the VLDB Endowment	Di Yang, Maryam Hasan et al.	2
7	Glyph-based Visualization: Foundations, Design Guidelines, Techniques and Applications	Eurographics	Rita Borgo, Johannes Kehrer et al.	192
8	Quality-aware visual data analysis	Computational Statistics	Matthew Ward, Di Yang et al.	7
9	Measuring Data Abstraction Quality in Multiresolution Visualizations	IEEE Transactions on Visualization and Computer Graphics	Matthew Ward, Elke A. Rundensteiner et al.	68
10	Semantic Image Browser: Bridging Information Visualization with Automated Intelligent Image Analysis		Jing Yang, Jianping Fan et al.	50
11	A pictorial database management system wuich uses histogram classification as a similarity measure		Matthew Ward et al.	0
12	A general framework for multi-resolution visualization		Matthew Ward, Elke A. Rundensteiner et al.	1
13	Information and scientific visualization: separate but equal or happy together at last	IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control	Theresa-Marie Rhyne, Melanie Tory et al.	12
14	Finding needles in large-scale multivariate data haystacks	IEEE Computer Graphics and Applications	Matthew Ward	9
15	Interaction spaces in data and information visualization		Matthew Ward, Jing Yang	23
16	Hierarchical visual data mining for large-scale data	Computational Statistics	Matthew Ward, Wei Peng et al.	4
17	A visual programming environment for supporting scientific data analysis		Matthew Ward, Michael A. Gennert et al.	3
18	Computational Methods for Single‐Point and Multipoint Analysis of Genetic Variants Associated with a Simulated Complex Disorder in a General Population	Genetic Epidemiology	Manish Pungliya, Michael A. Sao Pedro et al.	4
19	Geo Viser. Geographic visualization of search engine results		Matthew Ward et al.	2
20	Cartographic Character Recognition	Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE	Matthew Ward et al.	1

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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