William Millar

510 citations
19 papers · 249 indexed · h-index 9

Impact in

Papers in

William Millar

15 papers receiving 223 citations

Peers

William Millar
Comparison fields: 5 of 46
  • Software 25
  • Artificial Intelligence 136
  • Computer Networks and Communications 88
  • Hardware and Architecture 19
  • Control and Systems Engineering 52
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Citations per year

Countries citing papers authored by William Millar

Since Specialization
Citations

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

Fields of papers citing papers by William Millar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside William Millar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with William Millar Line = papers co-authored together William Millar links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 200261
2 199957
3 199922
4 199822
5
Remote agent: an autonomous control system for the New Millennium
200021
6
Decompositional, model-based learning and its analogy to diagnosis
199816
7 196414
8 202212
9 20199
10 20204
11
Remote Agent Experiment
20004
12 19993
13 19552
14 19871
15 20211
16 20210
17 20240
18 20180
19
Feature extraction in the machine recognition of speech
19810

About William Millar

William Millar is a scholar working on Artificial Intelligence, Computer Networks and Communications, Aerospace Engineering, Ocean Engineering and Atomic and Molecular Physics, and Optics, having authored 19 papers that have together received 249 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (8 papers), Gyrotron and Vacuum Electronics Research (4 papers), Particle Accelerators and Free-Electron Lasers (4 papers), Particle accelerators and beam dynamics (4 papers), Logic, Reasoning, and Knowledge (3 papers), Speech Recognition and Synthesis (3 papers), Reservoir Engineering and Simulation Methods (2 papers) and Distributed systems and fault tolerance (2 papers). The work is most often cited by research in Software (25 citations), Artificial Intelligence (136 citations), Computer Networks and Communications (88 citations), Hardware and Architecture (19 citations) and Control and Systems Engineering (52 citations). William Millar has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Edward B. Gamble, Brian C. Williams, James Kurien, Bob Kanefsky, Gregory A. Dorais, Nicola Muscettola, Kanna Rajan, Douglas E. Bernard, P. Pandurang Nayak and Andrew S. Paton. Their work appears in journals such as Physical Review Accelerators and Beams, Journal of Applied Physics, Autonomous Agents and Multi-Agent Systems, JACOW and CERN Document Server (European Organization for Nuclear Research).

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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