Bill Baird

802 total citations
29 papers, 572 citations indexed

About

Bill Baird is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, Bill Baird has authored 29 papers receiving a total of 572 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cognitive Neuroscience, 12 papers in Artificial Intelligence and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Bill Baird's work include Neural dynamics and brain function (15 papers), Neural Networks and Applications (12 papers) and Olfactory and Sensory Function Studies (4 papers). Bill Baird is often cited by papers focused on Neural dynamics and brain function (15 papers), Neural Networks and Applications (12 papers) and Olfactory and Sensory Function Studies (4 papers). Bill Baird collaborates with scholars based in United States, Canada and United Kingdom. Bill Baird's co-authors include Walter Freeman, Walter J. Freeman, Frank H. Eeckman, Morris W. Hirsch, Marram P. Olson, Michael Trumpis, Don L. Jewett, Linda Larson‐Prior, Gideon P. Caplovitz and Laura Rees and has published in prestigious journals such as Behavioral Neuroscience, Neurocomputing and Clinical Neurophysiology.

In The Last Decade

Bill Baird

28 papers receiving 535 citations

Peers

Bill Baird
Comparison fields: 5 of 88
  • Cognitive Neuroscience 399
  • Artificial Intelligence 162
  • Cellular and Molecular Neuroscience 105
  • Statistical and Nonlinear Physics 87
  • Sensory Systems 82
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Citations per field, relative to Bill Baird
Bill Baird · 1×
Citations per year, relative to Bill Baird
Bill Baird · 1×

Countries citing papers authored by Bill Baird

Since Specialization
Citations

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

Fields of papers citing papers by Bill Baird

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bill Baird

This figure shows the co-authorship network connecting the top 25 collaborators of Bill Baird. A scholar is included among the top collaborators of Bill Baird 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 Baird. Bill Baird 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 18
2 6
3 23
4 43
5
Integrated Science and Math for Junior High Teacher Preparation: Staff Development as a Continual Process.
1
6
Synchronized Auditory and Cognitive 40 Hz Attentional Streams, and the Impact of Rhythmic Expectation on Auditory Scene Analysis
1
7 11
8
A normal form projection algorithm for associative memory
10
9
Effects of applied electric current fields on cortical neural activity
7
10
Synchronization and Grammatical Inference in an Oscillating Elman Net
2
11
Bifurcation and category learning in network models of oscillating cortex
1
12 2
13 4
14
CAM Storage of Analog Patterns and Continuous Sequences with 3N2 Weights
1
15 7
16
Associative Memory in a Simple Model of Oscillating Cortex
7
17
Careers in Computing: A Kit for Teachers, Counselors, and Volunteers.
1
18
A Bifurcation Theory Approach to the Programming of Periodic Attractors in Network Models of Olfactory Cortex
7
19 134
20 112

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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