Subhro Roy

1.3k citations
25 papers · 741 · h-index 11

Impact in

Papers in

    • Topic Modeling 20
    • Natural Language Processing Techniques 17
    • Speech and dialogue systems 4
    • AI-based Problem Solving and Planning 3
    • Reinforcement Learning in Robotics 2
    • Text Readability and Simplification 2
    • Multimodal Machine Learning Applications 5

Subhro Roy

23 papers receiving 709 citations

Peers

Subhro Roy
Comparison fields: 5 of 52
  • Artificial Intelligence 645
  • Computer Vision and Pattern Recognition 137
  • Information Systems 147
  • Computational Theory and Mathematics 65
  • Computer Science Applications 14
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Citations per field
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Citations per year

Countries citing papers authored by Subhro Roy

Since Specialization
Citations

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

Fields of papers citing papers by Subhro Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015165
2 2016121
3 202187
4 201585
5 201760
6 201858
7 201430
8 202028
9 201620
10
Grounding Robot Plans from Natural Language Instructions with Incomplete World Knowledge
201815
11 201610
12
Illinois CCG TAC 2015 Event Nugget, Entity Discovery and Linking, and Slot Filler Validation Systems
20159
13 20218
14 20238
15 20196
16 20226
17 20226
18 20165
19
Task-Conditioned Variational Autoencoders for Learning Movement Primitives
20194
20
Inferring Task Goals and Constraints using Bayesian Nonparametric Inverse Reinforcement Learning
20194

About Subhro Roy

Subhro Roy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computational Theory and Mathematics and Computer Networks and Communications, having authored 25 papers that have together received 741 indexed citations. Recurring topics across this work include Topic Modeling (20 papers), Natural Language Processing Techniques (17 papers), Multimodal Machine Learning Applications (5 papers), Speech and dialogue systems (4 papers), AI-based Problem Solving and Planning (3 papers), Software Engineering Research (3 papers), Reinforcement Learning in Robotics (2 papers) and Text Readability and Simplification (2 papers). The work is most often cited by research in Artificial Intelligence (645 citations), Computer Vision and Pattern Recognition (137 citations), Information Systems (147 citations), Computational Theory and Mathematics (65 citations) and Computer Science Applications (14 citations). Subhro Roy has collaborated with scholars based in United States, India and Bangladesh. Frequent co-authors include Dan Roth, Tim Vieira, Hannaneh Hajishirzi, Rik Koncel-Kedziorski, Aida Amini, Nate Kushman, Charles Chen, Benjamin Van Durme, Daehyung Park and Dan Klein. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Theory and applications of categories, Algorithmica, The International Journal of Robotics Research and Results in Materials.

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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