Preeti Bajaj
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 10%
- Biomedical Engineering
- Experimental and Cognitive Psychology top 5%
- Automotive Engineering top 10%
- Co-authors
- Robert A. ScheidtJames L. PattonPrema DaigavaneRahul AgrawalAjith AbrahamLatesh MalikKenneth W. FishbeinRichard G. Spencer
- Topics
- Neural Networks and Applications (9 papers)Embedded Systems Design Techniques (9 papers)Sleep and Work-Related Fatigue (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEFEBS Letters
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Preeti Bajaj
86 papers receiving 902 citations
Peers
Comparison fields: 5 of 124
- Computer Vision and Pattern Recognition 204
- Cognitive Neuroscience 178
- Biomedical Engineering 174
- Experimental and Cognitive Psychology 166
- Automotive Engineering 124
Countries citing papers authored by Preeti Bajaj
This map shows the geographic impact of Preeti Bajaj'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 Preeti Bajaj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Preeti Bajaj more than expected).
Fields of papers citing papers by Preeti Bajaj
This network shows the impact of papers produced by Preeti Bajaj. 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 Preeti Bajaj. The network helps show where Preeti Bajaj may publish in the future.
Co-authorship network of co-authors of Preeti Bajaj
This figure shows the co-authorship network connecting the top 25 collaborators of Preeti Bajaj. A scholar is included among the top collaborators of Preeti Bajaj 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 Preeti Bajaj. Preeti Bajaj 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 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | Optimization of Traffic Flow through Signalized Intersections using PSO | 3 |
| 12 | 59 | |
| 13 | “Environmentally Conscious Consumer Behavior: An Empirical Study” | 2 |
| 14 | 14 | |
| 15 | Human Perception-based Color Image Segmentation Using Comprehensive Learning Particle Swarm Optimization. | 28 |
| 16 | 5 | |
| 17 | Approach for VHDL and FPGA Implementation of Communication Controller of FlexRay Controller. | 1 |
| 18 | 20 | |
| 19 | 24 | |
| 20 | 33 |
About Preeti Bajaj
Preeti Bajaj is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 96 papers that have together received 985 indexed citations. Recurring topics across this work include Neural Networks and Applications (9 papers), Embedded Systems Design Techniques (9 papers) and Sleep and Work-Related Fatigue (8 papers). The work is most often cited by research in Human-Computer Interaction (75 citations), Experimental and Cognitive Psychology (166 citations) and Rehabilitation (76 citations). Preeti Bajaj has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Robert A. Scheidt, James L. Patton, Prema Daigavane, Rahul Agrawal, Ajith Abraham, Latesh Malik, Kenneth W. Fishbein, Richard G. Spencer, Avadhesha Surolia and K. Suguna. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and FEBS Letters.
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.