Niki Parmar
- Artificial Intelligence top 1%
- Signal Processing top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Yonghui WuZhengdong ZhangJames QinAnmol GulatiRuoming PangChung‐Cheng ChiuWei HanShibo Wang
- Topics
- Social and Intergroup Psychology (1 paper)Cultural Differences and Values (1 paper)Advanced Text Analysis Techniques (1 paper)
- Journals
- Journal of Experimental Psychology GeneralBehavior Research Methods2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
- Partner nations
- United StatesCanada
In The Last Decade
Niki Parmar
6 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Artificial Intelligence 1.3k
- Signal Processing 904
- Computer Vision and Pattern Recognition 271
- Cognitive Neuroscience 92
- Experimental and Cognitive Psychology 92
Countries citing papers authored by Niki Parmar
This map shows the geographic impact of Niki Parmar'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 Niki Parmar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niki Parmar more than expected).
Fields of papers citing papers by Niki Parmar
This network shows the impact of papers produced by Niki Parmar. 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 Niki Parmar. The network helps show where Niki Parmar may publish in the future.
Co-authorship network of co-authors of Niki Parmar
This figure shows the co-authorship network connecting the top 25 collaborators of Niki Parmar. A scholar is included among the top collaborators of Niki Parmar 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 Niki Parmar. Niki Parmar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 70 | |
| 2 | Conformer: Convolution-augmented Transformer for Speech Recognitionbreakdown → | 1668 |
| 3 | Studying Stand-Alone Self-Attention in Vision Models | 3 |
| 4 | Towards a better understanding of Vector Quantized Autoencoders | 7 |
| 5 | 106 | |
| 6 | 16 |
About Niki Parmar
Niki Parmar is a scholar working on Computer Vision and Pattern Recognition, Social Psychology and Artificial Intelligence, having authored 6 papers that have together received 1.9k indexed citations. Recurring topics across this work include Social and Intergroup Psychology (1 paper), Cultural Differences and Values (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Signal Processing (904 citations), Artificial Intelligence (1.3k citations) and Computer Vision and Pattern Recognition (271 citations). Niki Parmar has collaborated with scholars based in United States and Canada. Frequent co-authors include Yonghui Wu, Zhengdong Zhang, James Qin, Anmol Gulati, Ruoming Pang, Chung‐Cheng Chiu, Wei Han, Shibo Wang, Yu Zhang and Jiahui Yu. Their work appears in journals such as Journal of Experimental Psychology General, Behavior Research Methods and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
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.