Niki Parmar

11.3k total citations · 1 hit paper
6 papers, 1.9k citations indexed

About

Niki Parmar is a scholar working on Artificial Intelligence, Social Psychology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Niki Parmar has authored 6 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Social Psychology and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Niki Parmar's work include Social and Intergroup Psychology (1 paper), Cultural Differences and Values (1 paper) and Advanced Text Analysis Techniques (1 paper). Niki Parmar is often cited by papers focused on Social and Intergroup Psychology (1 paper), Cultural Differences and Values (1 paper) and Advanced Text Analysis Techniques (1 paper). Niki Parmar collaborates with scholars based in United States and Canada. Niki Parmar's 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 and has published in prestigious journals such as Journal of Experimental Psychology General, Behavior Research Methods and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

In The Last Decade

Niki Parmar

6 papers receiving 1.8k citations

Hit Papers

Conformer: Convolution-augmented Transformer for Speech R... 2020 2026 2022 2024 2020 500 1000 1.5k

Peers

Niki Parmar
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
Replace Hagen Soltau with:
Hagen Soltau United States
Yasuo Ariki Japan
Arnab Ghoshal United States
Zhiyong Wu China
Gabriel Synnaeve France
William Chan United States
Chiori Hori Japan
James Qin United States
Hagen Soltau United States View profile →
Citations per field, relative to Niki Parmar
Niki Parmar · 1×
Citations per year, relative to Niki Parmar
Niki Parmar · 1×

Countries citing papers authored by Niki Parmar

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

6 of 6 papers shown
# Work Indexed citations
1 70
2
Conformer: Convolution-augmented Transformer for Speech Recognition breakdown →
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

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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