Numair Khan

640 citations
13 papers · 369 · 1 hit paper · h-index 6

Impact in

Papers in

Numair Khan

11 papers receiving 361 citations

Numair Khan's Hit Papers

Neural Fields in Visual Computing and Beyond 2022 · 285 citations
2850+1+2Years since publication50100150200250

Peers

Numair Khan
Comparison fields: 5 of 61
  • Computer Graphics and Computer-Aided Design 117
  • Computer Vision and Pattern Recognition 234
  • Computational Mechanics 113
  • Geology 18
  • Structural Biology 4
Replace Iro Laina with:
Iro Laina United Kingdom
Giulia Fracastoro Italy
Adrian Secord United States
Frederik Warburg Denmark
Lifan Wu United States
Kangle Deng United States
Martin Kiefel Germany
Matheus Gadelha United States
T.S. Yoo United States
D. Snow United States
Numair Khan relative to Iro Laina United Kingdom Iro Laina's profile →
Citations per field
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Citations per year

Countries citing papers authored by Numair Khan

Since Specialization
Citations

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

Fields of papers citing papers by Numair Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1
Neural Fields in Visual Computing and Beyond
Hit paper breakdown →
2022285
2 201727
3 201916
4 202510
5 20248
6 20205
7 20165
8 20174
9 20213
10 20233
11 20233
12 20240
13 20250

About Numair Khan

Numair Khan is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computational Mechanics, Statistical and Nonlinear Physics and Transportation, having authored 13 papers that have together received 369 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (9 papers), Computer Graphics and Visualization Techniques (4 papers), 3D Shape Modeling and Analysis (3 papers), Advanced Image Processing Techniques (3 papers), Opinion Dynamics and Social Influence (2 papers), Optical measurement and interference techniques (2 papers), Complex Network Analysis Techniques (2 papers) and Human Mobility and Location-Based Analysis (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (117 citations), Computer Vision and Pattern Recognition (234 citations), Computational Mechanics (113 citations), Geology (18 citations) and Structural Biology (4 citations). Numair Khan has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include James Tompkin, Shunsuke Saito, Or Litany, Vincent Sitzmann, Srinath Sridhar, Yiheng Xie, Federico Tombari, Towaki Takikawa, Anis Ur Rahman and Min H. Kim. Their work appears in journals such as International Journal of Computer Vision, Pervasive and Mobile Computing, International Journal of Human-Computer Interaction, Computer Graphics Forum and Adelaide Research & Scholarship (AR&S) (University of Adelaide).

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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