Amirsina Torfi

578 citations
8 papers · 169 indexed · h-index 4
Topics
Speech and Audio Processing (4 papers)Music and Audio Processing (4 papers)Machine Learning in Healthcare (3 papers)
Partner nations
United States

In The Last Decade

Amirsina Torfi

8 papers receiving 163 citations

Peers

Amirsina Torfi
Comparison fields: 5 of 56
  • Artificial Intelligence 98
  • Computer Vision and Pattern Recognition 57
  • Signal Processing 50
  • Health Informatics 13
  • Electrical and Electronic Engineering 12
Replace T. Kar with:
T. Kar India
Mohamed Uvaze Ahamed Ayoobkhan India
Negar Rostamzadeh United States
Meng Zhao China
A Prathik India
M. Shamim Kaiser Bangladesh
Koushick Barua Bangladesh
Matt Sharifi United States
Christopher Akiki Germany
Alfredo Nazábal United Kingdom
Amirsina Torfi relative to T. Kar India T. Kar's profile →
Citations per field
00.5×3.4×
T. Kar · 1×
Citations per year

Countries citing papers authored by Amirsina Torfi

Since Specialization
Citations

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

Fields of papers citing papers by Amirsina Torfi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amirsina Torfi. 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 Amirsina Torfi. The network helps show where Amirsina Torfi may publish in the future.

Co-authorship network of co-authors of Amirsina Torfi

This figure shows the co-authorship network connecting the top 25 collaborators of Amirsina Torfi. A scholar is included among the top collaborators of Amirsina Torfi 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 Amirsina Torfi. Amirsina Torfi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1 83
2
COR-GAN: Correlation-Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records.
3
3
Nearest Neighbor Classifier – From Theory to Practice
1
4
Generating Synthetic Healthcare Records Using Convolutional Generative Adversarial Networks
2
5 7
6 1
7
Coupled 3D Convolutional Neural Networks for Audio-Visual Recognition.
3
8 69

About Amirsina Torfi

Amirsina Torfi is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 169 indexed citations. Recurring topics across this work include Speech and Audio Processing (4 papers), Music and Audio Processing (4 papers) and Machine Learning in Healthcare (3 papers). The work is most often cited by research in Health Informatics (13 citations), Signal Processing (50 citations) and Artificial Intelligence (98 citations). Amirsina Torfi has collaborated with scholars based in United States. Frequent co-authors include Edward A. Fox, Chandan K. Reddy, Jeremy Dawson, Seyed Mehdi Iranmanesh and Nasser M. Nasrabadi. Their work appears in journals such as IEEE Access, Information Sciences and Figshare.

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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