David R. Miller
- Artificial Intelligence top 2%
- Speech Recognition and Synthesis 6
- Topic Modeling 4
- Natural Language Processing Techniques 4
- Signal Processing top 5%
- Speech and Audio Processing 4
- Cognitive Neuroscience top 10%
- Information Systems top 5%
- Global and Planetary Change top 10%
- Land Use and Ecosystem Services 5
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- Electoral Systems and Political Participation 8
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- Public Policy and Administration Research 5
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- Political Influence and Corporate Strategies 5
- Co-authors
- Ian D. BishopTim LeekRichard SchwartzMary H. BurlesonVictor S. JohnstonH. GishOwen KimballStephen A. Lowe
- Journals
- American Political Science Review (1 paper)Renewable Energy (1 paper)Landscape and Urban Planning (2 papers)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
David R. Miller
48 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 135
- Artificial Intelligence 639
- Signal Processing 197
- Cognitive Neuroscience 245
- Information Systems 219
- Global and Planetary Change 183
Countries citing papers authored by David R. Miller
This map shows the geographic impact of David R. Miller'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 David R. Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David R. Miller more than expected).
Fields of papers citing papers by David R. Miller
This network shows the impact of papers produced by David R. Miller. 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 David R. Miller. The network helps show where David R. Miller may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David R. Miller, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 6 | |
| 4 | 2021 | 6 | |
| 5 | 2021 | 7 | |
| 6 | 2018 | 35 | |
| 7 | 2018 | 7 | |
| 8 | 2015 | 7 | |
| 9 | 2007 | 191 | |
| 10 | 2002 | 12 | |
| 11 | 2001 | 39 | |
| 12 | 2000 | 36 | |
| 13 | Named Entity Extraction from Broadcast News | 1999 | 29 |
| 14 | BBN at TREC7: Using Hidden Markov Models for Information Retrieval. | 1998 | 32 |
| 15 | 1997 | 4 | |
| 16 | 1997 | 11 | |
| 17 | The School Counselor and Christian Fundamentalist Families. | 1995 | 3 |
| 18 | THE USE OF THE JAM ASSIGNMENT MODEL FOR URBAN SCHEME DESIGN AND EVALUATION | 1990 | 2 |
| 19 | COST COMPARISON OF BUSWAY AND RAILWAY RAPID TRANSIT | 1973 | 3 |
| 20 | Urban transportation policy : new perspectives | 1972 | 7 |
About David R. Miller
David R. Miller is a scholar working on Public Administration, Communication and Transportation, having authored 55 papers that have together received 1.6k indexed citations. Recurring topics across this work include Electoral Systems and Political Participation (8 papers), Speech Recognition and Synthesis (6 papers), Public Policy and Administration Research (5 papers), Land Use and Ecosystem Services (5 papers), Political Influence and Corporate Strategies (5 papers), Speech and Audio Processing (4 papers), Topic Modeling (4 papers) and Natural Language Processing Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (639 citations), Signal Processing (197 citations) and Cognitive Neuroscience (245 citations). David R. Miller has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Ian D. Bishop, Tim Leek, Richard Schwartz, Mary H. Burleson, Victor S. Johnston, Richard Schwartz, H. Gish, Owen Kimball, Stephen A. Lowe and Chia-Lin Kao. Their work appears in journals such as American Political Science Review, Renewable Energy and Landscape and Urban Planning.
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.