Bill Hibbard

548 total citations
31 papers, 228 citations indexed

About

Bill Hibbard is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Bill Hibbard has authored 31 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 9 papers in Computational Theory and Mathematics. Recurrent topics in Bill Hibbard's work include Data Visualization and Analytics (12 papers), Computability, Logic, AI Algorithms (9 papers) and Computer Graphics and Visualization Techniques (3 papers). Bill Hibbard is often cited by papers focused on Data Visualization and Analytics (12 papers), Computability, Logic, AI Algorithms (9 papers) and Computer Graphics and Visualization Techniques (3 papers). Bill Hibbard collaborates with scholars based in United States, Australia and Spain. Bill Hibbard's co-authors include Michael Böttinger, Chris R. Johnson, Joachim Biercamp, Martin G. Schultz, Chaomei Chen, Theresa-Marie Rhyne, Stephen G. Eick, José Hernández‐Orallo, David L. Dowe and Wayne F. Feltz and has published in prestigious journals such as Communications of the ACM, IEEE Computer Graphics and Applications and ACM SIGGRAPH Computer Graphics.

In The Last Decade

Bill Hibbard

30 papers receiving 196 citations

Peers

Bill Hibbard
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 81
  • Artificial Intelligence 77
  • Computational Theory and Mathematics 35
  • Computer Graphics and Computer-Aided Design 34
  • Cognitive Neuroscience 31
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Shurui Gui China
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Çağatay Demiralp United States
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Citations per field, relative to Bill Hibbard
Bill Hibbard · 1×
Citations per year, relative to Bill Hibbard
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Countries citing papers authored by Bill Hibbard

Since Specialization
Citations

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

Fields of papers citing papers by Bill Hibbard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bill Hibbard

This figure shows the co-authorship network connecting the top 25 collaborators of Bill Hibbard. A scholar is included among the top collaborators of Bill Hibbard 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 Bill Hibbard. Bill Hibbard 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
# Work Indexed citations
1
Self-Modeling Agents and Reward Generator Corruption
3
2
Turing machines and recursive Turing Tests
1
3
Nietzsche's Overhuman is an Ideal Whereas Posthumans Will be Real
3
4
Adversarial Sequence Prediction
7
5
Open Source AI
3
6
Can we determine the top unresolved problems of visualization
4
7
Reinforcement Learning as a Context for Integrating AI Research.
0
8 5
9 1
10 3
11 5
12 11
13 10
14 13
15 2
16 21
17 8
18 1
19
Retrieval and Visualization of AERIPLUS Temperature and Moisture Profiles for Assimilation into ARM Single-Column Models
3
20 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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