Ashwin P. Dani

76 papers receiving 1.1k citations

Peers

Ashwin P. Dani
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 482
  • Control and Systems Engineering 443
  • Aerospace Engineering 371
  • Media Technology 103
  • Computer Networks and Communications 213
Replace Huimin Lu with:
Huimin Lu China
H. R. Everett United States
Jinzhu Peng China
Gian Luca Mariottini United States
Shuhuan Wen China
Jing Yuan China
Haoyao Chen China
Alfredo Gardel Spain
Lei Yu China
Xinhan Huang China
Ashwin P. Dani relative to Huimin Lu China Huimin Lu's profile →
Citations per field
00.5×3.1×
Huimin Lu · 1×
Citations per year

Countries citing papers authored by Ashwin P. Dani

Since Specialization
Citations

This map shows the geographic impact of Ashwin P. Dani'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 Ashwin P. Dani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashwin P. Dani more than expected).

Fields of papers citing papers by Ashwin P. Dani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashwin P. Dani. 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 Ashwin P. Dani. The network helps show where Ashwin P. Dani may publish in the future.

Co-authors

The 25 scholars most cited alongside Ashwin P. Dani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ashwin P. Dani Line = papers co-authored together Ashwin P. Dani links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011116
2 201188
3 201387
4 201452
5 201151
6 201545
7 201641
8 202034
9 201531
10 201027
11 201124
12 201823
13 201320
14 201017
15 201517
16 201517
17
Learning Partially Contracting Dynamical Systems from Demonstrations
201716
18 202016
19 201815
20
Bayesian human intention inference through multiple model filtering with gaze-based priors
201615

About Ashwin P. Dani

Ashwin P. Dani is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Aerospace Engineering, Artificial Intelligence and Mechanical Engineering, having authored 81 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (33 papers), Robotics and Sensor-Based Localization (29 papers), Robot Manipulation and Learning (19 papers), Image Processing Techniques and Applications (11 papers), Distributed Control Multi-Agent Systems (7 papers), Teleoperation and Haptic Systems (7 papers), Adaptive Control of Nonlinear Systems (6 papers) and Target Tracking and Data Fusion in Sensor Networks (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (482 citations), Control and Systems Engineering (443 citations), Aerospace Engineering (371 citations), Media Technology (103 citations) and Computer Networks and Communications (213 citations). Ashwin P. Dani has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Warren E. Dixon, Harish Ravichandar, Nicholas Fischer, Zhen Kan, Soon‐Jo Chung, Seth Hutchinson, John M. Shea, Nitin Sharma, Dongkyoung Chwa and Nicholas Gans. Their work appears in journals such as IEEE Transactions on Automatic Control, Mechatronics, IEEE Transactions on Control Systems Technology, IEEE Transactions on Automation Science and Engineering and Automatica.

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.

Explore authors with similar magnitude of impact