Rohan Chandra

1.5k citations
21 papers · 699 · h-index 10

Impact in

Papers in

Rohan Chandra

20 papers receiving 676 citations

Peers

Rohan Chandra
Comparison fields: 5 of 75
  • Computer Vision and Pattern Recognition 404
  • Experimental and Cognitive Psychology 122
  • Signal Processing 74
  • Artificial Intelligence 218
  • Automotive Engineering 74
Replace Bernd Radig with:
Bernd Radig Germany
Peiyun Hu United States
Antonio Greco Italy
Titus Zaharia France
Thomas Zielke Germany
Loukas Bampis Greece
Luntian Mou China
Yaodong Cui Canada
Alina Roitberg Germany
Ioannis Kansizoglou Greece
Rohan Chandra relative to Bernd Radig Germany Bernd Radig's profile →
Citations per field
00.5×10×15×18.2×
Bernd Radig · 1×
Citations per year

Countries citing papers authored by Rohan Chandra

Since Specialization
Citations

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

Fields of papers citing papers by Rohan Chandra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rohan Chandra. 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 Rohan Chandra. The network helps show where Rohan Chandra may publish in the future.

Co-authors

The 25 scholars most cited alongside Rohan Chandra, 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 Rohan Chandra Line = papers co-authored together Rohan Chandra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020184
2 2020160
3 2022101
4 202293
5 202234
6 202431
7 202217
8 202514
9 202114
10 20239
11 20248
12
Emotions Don't Lie: A Deepfake Detection Method using Audio-Visual Affective Cues
20208
13 20237
14 20225
15 20245
16 20244
17 20252
18 20241
19 20251
20 20161

About Rohan Chandra

Rohan Chandra is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Control and Systems Engineering and Computer Networks and Communications, having authored 21 papers that have together received 699 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (6 papers), Reinforcement Learning in Robotics (5 papers), Autonomous Vehicle Technology and Safety (4 papers), Distributed Control Multi-Agent Systems (3 papers), Emotion and Mood Recognition (3 papers), Advanced Neural Network Applications (3 papers), Transportation and Mobility Innovations (2 papers) and Evacuation and Crowd Dynamics (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (404 citations), Experimental and Cognitive Psychology (122 citations), Signal Processing (74 citations), Artificial Intelligence (218 citations) and Automotive Engineering (74 citations). Rohan Chandra has collaborated with scholars based in United States, India and China. Frequent co-authors include Dinesh Manocha, Aniket Bera, Trisha Mittal, Uttaran Bhattacharya, Tianrui Guan, Adarsh Jagan Sathyamoorthy, Jun Wang, Larry S. Davis, Shiyi Lan and Zuxuan Wu. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Transactions on Intelligent Transportation Systems, Autonomous Robots, College Mathematics Journal and 2022 International Conference on Robotics and Automation (ICRA).

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.

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