Alark Joshi

945 citations
48 papers · 601 · h-index 13

Impact in

Papers in

Alark Joshi

42 papers receiving 584 citations

Peers

Alark Joshi
Comparison fields: 5 of 127
  • Computer Graphics and Computer-Aided Design 96
  • Computer Vision and Pattern Recognition 256
  • Cognitive Neuroscience 117
  • Signal Processing 58
  • Computer Science Applications 23
Replace Ziyu Wan with:
Ziyu Wan Hong Kong
Çağatay Demiralp United States
Nataniel Ruiz United States
Shintami Chusnul Hidayati Indonesia
Jason F. Shepherd United States
Kai Lawonn Germany
Daming Wei Japan
Shiaofen Fang United States
Theresa-Marie Rhyne United States
Daniele Marini Italy
Alark Joshi relative to Ziyu Wan Hong Kong Ziyu Wan's profile →
Citations per field
00.5×10×20×30×43×
Ziyu Wan · 1×
Citations per year

Countries citing papers authored by Alark Joshi

Since Specialization
Citations

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

Fields of papers citing papers by Alark Joshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Alark Joshi, 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 Alark Joshi Line = papers co-authored together Alark Joshi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011161
2 200653
3 202242
4 200733
5 200732
6 200632
7 201529
8 201727
9 201824
10 200821
11 200818
12 200615
13 200514
14 200811
15 200810
16 20059
17 20187
18 20226
19 20245
20 20185

About Alark Joshi

Alark Joshi is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computer Science Applications, Artificial Intelligence and Education, having authored 48 papers that have together received 601 indexed citations. Recurring topics across this work include Data Visualization and Analytics (18 papers), Computer Graphics and Visualization Techniques (12 papers), Teaching and Learning Programming (5 papers), Advanced Vision and Imaging (4 papers), Online Learning and Analytics (4 papers), Medical Image Segmentation Techniques (4 papers), Augmented Reality Applications (4 papers) and Multimedia Communication and Technology (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (96 citations), Computer Vision and Pattern Recognition (256 citations), Cognitive Neuroscience (117 citations), Signal Processing (58 citations) and Computer Science Applications (23 citations). Alark Joshi has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Penny Rheingans, Xenophon Papademetris, Dustin Scheinost, Lawrence H. Staib, Jesus J. Caban, Hirohito Okuda, Robert S. Laramee, Paul Nagy, Anita Komlódi and John R. Goodall. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Computer Graphics and Applications, Journal of Digital Imaging, BMC Bioinformatics and Behavior Research Methods.

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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