Mohak Shah
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Automotive Engineering top 10%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Unmesh KurupJunyao GuoYiming XiaoSimon FrancisTal ArbelDouglas L. ArnoldNagesh K. SubbannaD. Louis Collins
- Topics
- Data Stream Mining Techniques (5 papers)Machine Learning and Data Classification (5 papers)IoT and Edge/Fog Computing (4 papers)
- Journals
- PLoS ONEIEEE Transactions on Intelligent Transportation SystemsJournal of the Franklin Institute
- Partner nations
- United StatesCanadaSouth Korea
In The Last Decade
Mohak Shah
24 papers receiving 523 citations
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 176
- Computer Vision and Pattern Recognition 159
- Computer Networks and Communications 101
- Automotive Engineering 87
- Radiology, Nuclear Medicine and Imaging 62
Countries citing papers authored by Mohak Shah
This map shows the geographic impact of Mohak Shah'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 Mohak Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohak Shah more than expected).
Fields of papers citing papers by Mohak Shah
This network shows the impact of papers produced by Mohak Shah. 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 Mohak Shah. The network helps show where Mohak Shah may publish in the future.
Co-authorship network of co-authors of Mohak Shah
This figure shows the co-authorship network connecting the top 25 collaborators of Mohak Shah. A scholar is included among the top collaborators of Mohak Shah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohak Shah. Mohak Shah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 84 | |
| 4 | Multiclass Learning from Contradictions | 6 |
| 5 | 143 | |
| 6 | 8 | |
| 7 | 39 | |
| 8 | 1 | |
| 9 | 24 | |
| 10 | 7 | |
| 11 | 15 | |
| 12 | 10 | |
| 13 | 3 | |
| 14 | 14 | |
| 15 | 116 | |
| 16 | 6 | |
| 17 | Hold-out Risk Bounds for Classifier Performance Evaluation | 2 |
| 18 | 4 | |
| 19 | Risk Bounds for Randomized Sample Compressed Classifiers | 1 |
| 20 | 1 |
About Mohak Shah
Mohak Shah is a scholar working on Artificial Intelligence, Computer Science Applications and Computer Networks and Communications, having authored 24 papers that have together received 545 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (5 papers), Machine Learning and Data Classification (5 papers) and IoT and Edge/Fog Computing (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (159 citations), Automotive Engineering (87 citations) and Neurology (46 citations). Mohak Shah has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Unmesh Kurup, Junyao Guo, Yiming Xiao, Simon Francis, Tal Arbel, Douglas L. Arnold, Nagesh K. Subbanna, D. Louis Collins, Samarth Tripathi and Jacques Corbeil. Their work appears in journals such as PLoS ONE, IEEE Transactions on Intelligent Transportation Systems and Journal of the Franklin Institute.
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.