Vijay Vasudevan
About
In The Last Decade
Vijay Vasudevan
30 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Computer Networks and Communications 1.2k
- Computer Vision and Pattern Recognition 1.2k
- Artificial Intelligence 1.1k
- Information Systems 925
- Electrical and Electronic Engineering 253
Countries citing papers authored by Vijay Vasudevan
This map shows the geographic impact of Vijay Vasudevan'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 Vijay Vasudevan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vijay Vasudevan more than expected).
Fields of papers citing papers by Vijay Vasudevan
This network shows the impact of papers produced by Vijay Vasudevan. 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 Vijay Vasudevan. The network helps show where Vijay Vasudevan may publish in the future.
Co-authorship network of co-authors of Vijay Vasudevan
This figure shows the co-authorship network connecting the top 25 collaborators of Vijay Vasudevan. A scholar is included among the top collaborators of Vijay Vasudevan 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 Vijay Vasudevan. Vijay Vasudevan 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 | 4 | |
| 3 | 20 | |
| 4 | 16 | |
| 5 | 47 | |
| 6 | 33 | |
| 7 | Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset breakdown → | 300 |
| 8 | AutoAugment: Learning Augmentation Strategies From Data breakdown → | 1464 |
| 9 | Understanding and Simplifying One-Shot Architecture Search breakdown → | 234 |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 2 | |
| 13 | Neural optimizer search with reinforcement learning | 37 |
| 14 | Florida mammographer disability training vs needs. | 1 |
| 15 | 36 | |
| 16 | 38 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | Measurement and analysis of TCP throughput collapse in cluster-based storage systems | 203 |
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.