Phil Kim
Impact in
- Artificial Intelligence top 10%
- AI-based Problem Solving and Planning
Papers in
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- AI-based Problem Solving and Planning 2
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- Fault Detection and Control Systems 2
- Co-authors
- Brian Williams (1 shared paper)Wonhyuk Cho (2 shared papers)In Yang (1 shared paper)Michael Hofbaur (1 shared paper)Tobin Im (2 shared papers)Jinhyun Kim (1 shared paper)Jeongsik Kim (1 shared paper)Jung‐Hoon Kim (1 shared paper)
- Journals
- The Journal of Urology (1 paper)Public Personnel Management (1 paper)Review of Public Personnel Administration (1 paper)International Journal of Aeronautical and Space Sciences (1 paper)Asian Journal of Political Science (1 paper)
- Partner nations
- South KoreaNew ZealandUnited States
In The Last Decade
Phil Kim
12 papers receiving 386 citations
Peers
Comparison fields: 5 of 110
- Software 17
- Artificial Intelligence 123
- Computer Vision and Pattern Recognition 53
- Control and Systems Engineering 56
- Public Administration 8
Countries citing papers authored by Phil Kim
This map shows the geographic impact of Phil Kim'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 Phil Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phil Kim more than expected).
Fields of papers citing papers by Phil Kim
This network shows the impact of papers produced by Phil Kim. 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 Phil Kim. The network helps show where Phil Kim may publish in the future.
Co-authors
The 20 scholars most cited alongside Phil Kim, 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 | 2017 | 229 | |
| 2 | Executing reactive, model-based programs through graph-based temporal planning | 2001 | 67 |
| 3 | Kalman Filter for Beginners: with MATLAB Examples | 2011 | 63 |
| 4 | 2022 | 23 | |
| 5 | Model-based Reactive Programming of Cooperative Vehicles for Mars Exploration | 2001 | 10 |
| 6 | 2021 | 6 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 4 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 1 | |
| 11 | 2010 | 1 | |
| 12 | 2020 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2021 | 0 |
About Phil Kim
Phil Kim is a scholar working on Artificial Intelligence, Control and Systems Engineering, Sociology and Political Science, Public Administration and Aerospace Engineering, having authored 14 papers that have together received 413 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (2 papers), Fault Detection and Control Systems (2 papers), Public Policy and Administration Research (2 papers), Intestinal Malrotation and Obstruction Disorders (1 paper), Inertial Sensor and Navigation (1 paper), Distributed systems and fault tolerance (1 paper), Occupational Health and Performance (1 paper) and Renal and related cancers (1 paper). The work is most often cited by research in Software (17 citations), Artificial Intelligence (123 citations), Computer Vision and Pattern Recognition (53 citations), Control and Systems Engineering (56 citations) and Public Administration (8 citations). Phil Kim has collaborated with scholars based in South Korea, New Zealand and United States. Frequent co-authors include Brian Williams, Wonhyuk Cho, In Yang, Michael Hofbaur, Tobin Im, Jinhyun Kim, Jeongsik Kim, Jung‐Hoon Kim, Seungkeun Kim and Brian C. Williams. Their work appears in journals such as The Journal of Urology, Public Personnel Management, Review of Public Personnel Administration, International Journal of Aeronautical and Space Sciences and Asian Journal of Political Science.
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.