Ashutosh Mishra
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Biophysics top 10%
- Information Systems
- Co-authors
- Nimesh B. PatelM. SaleemDinesh VarshneyPartha ChakrabartiVijay Pratap SinghKavita KavitaDebabrata DashMadhukar Rai
- Topics
- Software Engineering Research (8 papers)Machine Learning in Bioinformatics (3 papers)Advanced Software Engineering Methodologies (3 papers)
- Journals
- Journal of Biological ChemistryExpert Systems with ApplicationsJournal of Applied Mechanics
- Partner nations
- IndiaUnited KingdomFinland
In The Last Decade
Ashutosh Mishra
31 papers receiving 253 citations
Peers
Comparison fields: 5 of 77
- Computer Vision and Pattern Recognition 115
- Artificial Intelligence 101
- Radiology, Nuclear Medicine and Imaging 53
- Biophysics 29
- Information Systems 28
Countries citing papers authored by Ashutosh Mishra
This map shows the geographic impact of Ashutosh Mishra'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 Ashutosh Mishra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashutosh Mishra more than expected).
Fields of papers citing papers by Ashutosh Mishra
This network shows the impact of papers produced by Ashutosh Mishra. 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 Ashutosh Mishra. The network helps show where Ashutosh Mishra may publish in the future.
Co-authorship network of co-authors of Ashutosh Mishra
This figure shows the co-authorship network connecting the top 25 collaborators of Ashutosh Mishra. A scholar is included among the top collaborators of Ashutosh Mishra 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 Ashutosh Mishra. Ashutosh Mishra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 15 | |
| 13 | 8 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 9 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 23 |
About Ashutosh Mishra
Ashutosh Mishra is a scholar working on Computer Science Applications, Information Systems and Software, having authored 38 papers that have together received 272 indexed citations. Recurring topics across this work include Software Engineering Research (8 papers), Machine Learning in Bioinformatics (3 papers) and Advanced Software Engineering Methodologies (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (115 citations), Biophysics (29 citations) and Software (12 citations). Ashutosh Mishra has collaborated with scholars based in India, United Kingdom and Finland. Frequent co-authors include Nimesh B. Patel, M. Saleem, Dinesh Varshney, Partha Chakrabarti, Vijay Pratap Singh, Kavita Kavita, Debabrata Dash, Madhukar Rai, Kirti Sharma and Sarthak Sahoo. Their work appears in journals such as Journal of Biological Chemistry, Expert Systems with Applications and Journal of Applied Mechanics.
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.