Nakul Gopalan

752 citations
23 papers · 381 indexed · h-index 11
Topics
Multimodal Machine Learning Applications (8 papers)Robotic Path Planning Algorithms (6 papers)Reinforcement Learning in Robotics (5 papers)

In The Last Decade

Nakul Gopalan

20 papers receiving 366 citations

Peers

Nakul Gopalan
Comparison fields: 5 of 74
  • Artificial Intelligence 241
  • Computer Vision and Pattern Recognition 148
  • Control and Systems Engineering 113
  • Social Psychology 49
  • Aerospace Engineering 23
Replace Francisco Cruz with:
Francisco Cruz Australia
Shane Griffith United States
Rogerio Bonatti United States
Dylan Hadfield-Menell United States
Halit Bener Suay United States
Ishika Singh United States
Arthur Bucker United Kingdom
Ce Zheng China
Tingwu Wang Canada
David Ha United States
Nakul Gopalan relative to Francisco Cruz Australia Francisco Cruz's profile →
Citations per field
00.5×1.5×2.4×
Francisco Cruz · 1×
Citations per year

Countries citing papers authored by Nakul Gopalan

Since Specialization
Citations

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

Fields of papers citing papers by Nakul Gopalan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nakul Gopalan

This figure shows the co-authorship network connecting the top 25 collaborators of Nakul Gopalan. A scholar is included among the top collaborators of Nakul Gopalan 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 Nakul Gopalan. Nakul Gopalan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 21
4 4
5 4
6 50
7 0
8 5
9 1
10 5
11 14
12 3
13 14
14 32
15 19
16 19
17 13
18 28
19 24
20 5

About Nakul Gopalan

Nakul Gopalan is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Family Practice, having authored 23 papers that have together received 381 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (8 papers), Robotic Path Planning Algorithms (6 papers) and Reinforcement Learning in Robotics (5 papers). The work is most often cited by research in Health Informatics (20 citations), Artificial Intelligence (241 citations) and Computer Vision and Pattern Recognition (148 citations). Nakul Gopalan has collaborated with scholars based in United States, Singapore and Germany. Frequent co-authors include Stefanie Tellex, Cynthia Matuszek, Hadas Kress‐Gazit, Matthew Gombolay, Andrew Silva, Lawson L. S. Wong, Mariah Schrum, Thao Nguyen, Roma Patel and Ellie Pavlick. Their work appears in journals such as Autonomous Robots, IEEE Robotics and Automation Letters and Pediatric Neurology.

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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