Nital S. Patel

467 citations
35 papers · 328 indexed · h-index 11

Nital S. Patel

31 papers receiving 313 citations

Peers

Nital S. Patel
Comparison fields: 5 of 57
  • Industrial and Manufacturing Engineering 135
  • Statistics, Probability and Uncertainty 93
  • Control and Systems Engineering 132
  • Signal Processing 33
  • Artificial Intelligence 74
Replace Tzyy‐Shuh Chang with:
Tzyy‐Shuh Chang United States
S. Tsutsui Japan
Ling-po Li China
Takehisa Kohda Japan
Nadia Salvatore Italy
K. Wojtek Przytula United States
Feng Xie China
Wu Song China
R. Devanathan Singapore
Nital S. Patel relative to Tzyy‐Shuh Chang United States Tzyy‐Shuh Chang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Nital S. Patel

Since Specialization
Citations

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

Fields of papers citing papers by Nital S. Patel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nital S. Patel. 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 Nital S. Patel. The network helps show where Nital S. Patel may publish in the future.

Co-authorship network

The 19 scholars most cited alongside Nital S. Patel, 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 Nital S. Patel Line = papers co-authored together Nital S. Patel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20242
4 20154
5 20132
6 20104
7 20101
8 20075
9 20061
10 20050
11 20041
12 20046
13 200410
14 20021
15 20024
16 200065
17 199824
18 199616
19 19962
20 19951

About Nital S. Patel

Nital S. Patel is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Statistics, Probability and Uncertainty, having authored 35 papers that have together received 328 indexed citations. Recurring topics across this work include Advanced Control Systems Optimization (12 papers), Scheduling and Optimization Algorithms (7 papers), Control Systems and Identification (7 papers), Industrial Vision Systems and Defect Detection (6 papers), Fault Detection and Control Systems (5 papers), Advanced Manufacturing and Logistics Optimization (4 papers), Advanced Statistical Process Monitoring (4 papers) and Stability and Control of Uncertain Systems (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (135 citations), Statistics, Probability and Uncertainty (93 citations) and Control and Systems Engineering (132 citations). Nital S. Patel has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include John S. Baras, Martin Braun, Jessica Lin, Lina J. Karam, Jieping Ye, Sen Yang, Gerald A. Miller, Ravi Garg, Enrique Del Castillo and James Moyne. Their work appears in journals such as IEEE Transactions on Automatic Control, Engineering Applications of Artificial Intelligence and IEEE Transactions on Automation Science and Engineering.

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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