Pramod Abichandani
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Aerospace Engineering top 10%
- Control and Systems Engineering top 10%
- Electrical and Electronic Engineering
- Co-authors
- Deepan LoboMoshe KamHande Y. BensonDonald J. BucciPrateek ShekharEli FrommStephanie P. GoldsteinFengqing Zhang
- Topics
- Robotic Path Planning Algorithms (10 papers)Teaching and Learning Programming (6 papers)Distributed Control Multi-Agent Systems (4 papers)
- Cited by
- Computer Science ApplicationsComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Partner nations
- United StatesCanada
In The Last Decade
Pramod Abichandani
33 papers receiving 482 citations
Peers
Comparison fields: 5 of 93
- Computer Vision and Pattern Recognition 132
- Computer Networks and Communications 108
- Aerospace Engineering 106
- Control and Systems Engineering 74
- Electrical and Electronic Engineering 59
Countries citing papers authored by Pramod Abichandani
This map shows the geographic impact of Pramod Abichandani'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 Pramod Abichandani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pramod Abichandani more than expected).
Fields of papers citing papers by Pramod Abichandani
This network shows the impact of papers produced by Pramod Abichandani. 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 Pramod Abichandani. The network helps show where Pramod Abichandani may publish in the future.
Co-authorship network of co-authors of Pramod Abichandani
This figure shows the co-authorship network connecting the top 25 collaborators of Pramod Abichandani. A scholar is included among the top collaborators of Pramod Abichandani 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 Pramod Abichandani. Pramod Abichandani 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 | 3 | |
| 3 | 1 | |
| 4 | 7 | |
| 5 | 13 | |
| 6 | 3 | |
| 7 | 24 | |
| 8 | 9 | |
| 9 | 80 | |
| 10 | 14 | |
| 11 | 22 | |
| 12 | 10 | |
| 13 | 14 | |
| 14 | 4 | |
| 15 | 4 | |
| 16 | 27 | |
| 17 | 12 | |
| 18 | 3 | |
| 19 | 12 | |
| 20 | 15 |
About Pramod Abichandani
Pramod Abichandani is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition and Architecture, having authored 34 papers that have together received 497 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (10 papers), Teaching and Learning Programming (6 papers) and Distributed Control Multi-Agent Systems (4 papers). The work is most often cited by research in Computer Science Applications (38 citations), Computer Vision and Pattern Recognition (132 citations) and Human-Computer Interaction (33 citations). Pramod Abichandani has collaborated with scholars based in United States and Canada. Frequent co-authors include Deepan Lobo, Moshe Kam, Hande Y. Benson, Donald J. Bucci, Prateek Shekhar, Eli Fromm, Stephanie P. Goldstein, Fengqing Zhang, Evan M. Forman and Meghan L. Butryn. Their work appears in journals such as IEEE Access, Sensors and International Journal of Computer Vision.
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.