Nikhil Naik
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 2%
- Global and Planetary Change top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Health, Toxicology and Mutagenesis top 5%
- Co-authors
- Ramesh RaskarCésar A. HidalgoAli MadaniRichard SocherAndre EstevaJade PhilipoomAli MottaghiJeff Dean
- Topics
- Advanced Optical Sensing Technologies (8 papers)Random lasers and scattering media (7 papers)Urban, Neighborhood, and Segregation Studies (5 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsAmerican Economic Review
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Nikhil Naik
33 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Computer Vision and Pattern Recognition 607
- Artificial Intelligence 579
- Global and Planetary Change 410
- Radiology, Nuclear Medicine and Imaging 351
- Health, Toxicology and Mutagenesis 266
Countries citing papers authored by Nikhil Naik
This map shows the geographic impact of Nikhil Naik'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 Nikhil Naik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nikhil Naik more than expected).
Fields of papers citing papers by Nikhil Naik
This network shows the impact of papers produced by Nikhil Naik. 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 Nikhil Naik. The network helps show where Nikhil Naik may publish in the future.
Co-authorship network of co-authors of Nikhil Naik
This figure shows the co-authorship network connecting the top 25 collaborators of Nikhil Naik. A scholar is included among the top collaborators of Nikhil Naik 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 Nikhil Naik. Nikhil Naik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 19 | |
| 5 | 13 | |
| 6 | 2 | |
| 7 | Deep learning-enabled medical computer visionbreakdown → | 718 |
| 8 | 161 | |
| 9 | 5 | |
| 10 | Computer Vision and Real Estate: Do Looks Matter and Do Incentives Determine Looks | 1 |
| 11 | 197 | |
| 12 | 4 | |
| 13 | 210 | |
| 14 | 37 | |
| 15 | 3 | |
| 16 | 60 | |
| 17 | Streetscore -- Predicting the Perceived Safety of One Million Streetscapesbreakdown → | 291 |
| 18 | 55 | |
| 19 | 0 | |
| 20 | 4 |
About Nikhil Naik
Nikhil Naik is a scholar working on Acoustics and Ultrasonics, Instrumentation and Transportation, having authored 37 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Optical Sensing Technologies (8 papers), Random lasers and scattering media (7 papers) and Urban, Neighborhood, and Segregation Studies (5 papers). The work is most often cited by research in Health Informatics (110 citations), Acoustics and Ultrasonics (68 citations) and Instrumentation (179 citations). Nikhil Naik has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Ramesh Raskar, César A. Hidalgo, Ali Madani, Richard Socher, Andre Esteva, Jade Philipoom, Ali Mottaghi, Jeff Dean, Katherine Chou and Yun Liu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and American Economic Review.
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.