Thomas E. Potok
- Artificial Intelligence top 2%
- Neural Networks and Reservoir Computing 13
- Advanced Clustering Algorithms Research 8
- Semantic Web and Ontologies 7
- Information Systems top 5%
- Signal Processing top 5%
- Data Management and Algorithms 7
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- Mobile Agent-Based Network Management 7
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- Advanced Memory and Neural Computing 20
- Ferroelectric and Negative Capacitance Devices 18
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- Complex Network Analysis Techniques 9
Thomas E. Potok
100 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 725
- Information Systems 244
- Signal Processing 113
- Computer Vision and Pattern Recognition 209
- Computer Networks and Communications 200
Countries citing papers authored by Thomas E. Potok
This map shows the geographic impact of Thomas E. Potok'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 Thomas E. Potok with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas E. Potok more than expected).
Fields of papers citing papers by Thomas E. Potok
This network shows the impact of papers produced by Thomas E. Potok. 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 Thomas E. Potok. The network helps show where Thomas E. Potok may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Thomas E. Potok, 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 | 2023 | 1 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 3 | |
| 5 | 2022 | 1 | |
| 6 | 2021 | 19 | |
| 7 | 2020 | 20 | |
| 8 | 2019 | 46 | |
| 9 | 2016 | 7 | |
| 10 | Discovery, analysis, and characteristics of event impacts | 2008 | 1 |
| 11 | 2007 | 2 | |
| 12 | 2007 | 21 | |
| 13 | Agent Based Approach for Searching, Mining and Managing Enormous Amounts of Spatial Image Data | 2005 | 1 |
| 14 | Multi-Agent System Case Studies in Command and Control, Information Fusion and Datat Managment. | 2004 | 3 |
| 15 | Suitability of Agent-Based Systems for Command and Control in Fault-Tolerant, Safety-Critical Responsive Decision Networks. | 2003 | 11 |
| 16 | 2003 | 16 | |
| 17 | A MULTI-AGENT SPARE PART GROUPING SYSTEM FOR LOGISTICS OPTIMIZATION | 1999 | 1 |
| 18 | Development of a quantitative process model for object-oriented software development | 1996 | 2 |
| 19 | Development productivity for commercial software using object-oriented methods | 1995 | 4 |
| 20 | 1992 | 2 |
About Thomas E. Potok
Thomas E. Potok is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 104 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (20 papers), Ferroelectric and Negative Capacitance Devices (18 papers), Neural Networks and Reservoir Computing (13 papers), Complex Network Analysis Techniques (9 papers), Advanced Clustering Algorithms Research (8 papers), Mobile Agent-Based Network Management (7 papers), Data Management and Algorithms (7 papers) and Semantic Web and Ontologies (7 papers). The work is most often cited by research in Artificial Intelligence (725 citations), Information Systems (244 citations) and Signal Processing (113 citations). Thomas E. Potok has collaborated with scholars based in United States, Chile and Canada. Frequent co-authors include Xiaohui Cui, Robert M. Patton, Catherine D. Schuman, J. Parker Mitchell, Jinzhu Gao, Yu Jiao, Ali R. Hurson, Prasanna Date, Steven R. Young and James S. Plank. Their work appears in journals such as D-Lib Magazine, Scientific Reports, Photogrammetric Engineering & Remote Sensing, npj Computational Materials and Journal of Parallel and Distributed Computing.
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.