Deepak Gopinath
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Social Psychology
- Control and Systems Engineering
- Cognitive Neuroscience
- Co-authors
- Brenna ArgallSiddarth JainTadas BaltrušaitisLouis–Philippe MorencyBehnaz NojavanasghariJayanth KoushikGil WeinbergAllison Morgan
- Topics
- EEG and Brain-Computer Interfaces (2 papers)Traffic and Road Safety (2 papers)Human-Automation Interaction and Safety (2 papers)
- Journals
- Scientific ReportsIEEE Transactions on Neural Systems and Rehabilitation EngineeringRobotics and Autonomous Systems
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
Deepak Gopinath
8 papers receiving 289 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 130
- Computer Vision and Pattern Recognition 64
- Social Psychology 59
- Control and Systems Engineering 55
- Cognitive Neuroscience 53
Countries citing papers authored by Deepak Gopinath
This map shows the geographic impact of Deepak Gopinath'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 Deepak Gopinath with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepak Gopinath more than expected).
Fields of papers citing papers by Deepak Gopinath
This network shows the impact of papers produced by Deepak Gopinath. 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 Deepak Gopinath. The network helps show where Deepak Gopinath may publish in the future.
Co-authorship network of co-authors of Deepak Gopinath
This figure shows the co-authorship network connecting the top 25 collaborators of Deepak Gopinath. A scholar is included among the top collaborators of Deepak Gopinath 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 Deepak Gopinath. Deepak Gopinath 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 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 6 | |
| 7 | 5 | |
| 8 | 112 | |
| 9 | 17 | |
| 10 | 154 |
About Deepak Gopinath
Deepak Gopinath is a scholar working on Safety, Risk, Reliability and Quality, Cognitive Neuroscience and Radiological and Ultrasound Technology, having authored 10 papers that have together received 302 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (2 papers), Traffic and Road Safety (2 papers) and Human-Automation Interaction and Safety (2 papers). The work is most often cited by research in Human-Computer Interaction (36 citations), Artificial Intelligence (130 citations) and Experimental and Cognitive Psychology (53 citations). Deepak Gopinath has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Brenna Argall, Siddarth Jain, Tadas Baltrušaitis, Louis–Philippe Morency, Behnaz Nojavanasghari, Jayanth Koushik, Gil Weinberg, Allison Morgan, Shabnam Hakimi and Jonathan DeCastro. Their work appears in journals such as Scientific Reports, IEEE Transactions on Neural Systems and Rehabilitation Engineering and Robotics and Autonomous Systems.
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.