Arjun Majumdar

586 total citations
11 papers, 115 citations indexed

About

Arjun Majumdar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Arjun Majumdar has authored 11 papers receiving a total of 115 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Arjun Majumdar's work include Geographic Information Systems Studies (2 papers), Complex Network Analysis Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). Arjun Majumdar is often cited by papers focused on Geographic Information Systems Studies (2 papers), Complex Network Analysis Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). Arjun Majumdar collaborates with scholars based in United States, India and Germany. Arjun Majumdar's co-authors include Laura J. Brattain, Brian A. Telfer, Jonathan Scalera, Chad W. Farris, Miriam Cha, H. T. Kung, Stefan Lee, Harsh Agrawal, Dhruv Batra and Aravind Rajeswaran and has published in prestigious journals such as arXiv (Cornell University), PubMed and International Conference on Information Fusion.

In The Last Decade

Arjun Majumdar

8 papers receiving 111 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Arjun Majumdar United States	4	48	38	38	26	25	11	115
Hao Tan United States	7	7 0.1×	18 0.5×	2 0.1×	8 0.3×	8 0.3×	42	137
Raquel León Spain	10	7 0.1×	58 1.5×	5 0.1×	28 1.1×	12 0.5×	36	318
Fan Huang China	9	16 0.3×	7 0.2×	3 0.1×	13 0.5×	6 0.2×	24	253
Dejiang Xu Singapore	6	1 0.0×	37 1.0×	15 0.4×	9 0.3×	17 0.7×	15	252
Xinjun Ma China	4		17 0.4×	18 0.5×	3 0.1×	9 0.4×	4	125
Parham Khojasteh Australia	7	20 0.4×	35 0.9×		25 1.0×	4 0.2×	8	292
Henry A. Leopold Canada	6		26 0.7×	30 0.8×	8 0.3×	7 0.3×	10	259
Beatriz García Santa Cruz Luxembourg	4	18 0.4×	47 1.2×		7 0.3×	3 0.1×	6	97
Julian Krebs United States	4	1 0.0×	21 0.6×	10 0.3×	10 0.4×	7 0.3×	4	156

Countries citing papers authored by Arjun Majumdar

Since Specialization

Citations

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

Fields of papers citing papers by Arjun Majumdar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arjun Majumdar

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

All Works

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11 of 11 papers shown

1.

Wu, Tingfan, Arjun Majumdar, Vincent-Pierre Berges, et al.. (2024). What Do We Learn from a Large-Scale Study of Pre-Trained Visual Representations in Sim and Real Environments?. 17515–17521.

2.

Majumdar, Arjun, et al.. (2024). Stretch with Stretch: Physical Therapy Exercise Games Led by a Mobile Manipulator. 5569–5576.

3.

Majumdar, Arjun, et al.. (2023). Behavioral Analysis of Vision-and-Language Navigation Agents. 2574–2582. 2 indexed citations

4.

Majumdar, Arjun, et al.. (2021). SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation. arXiv (Cornell University). 34. 3 indexed citations

5.

Majumdar, Arjun, et al.. (2019). Earthquake Investigation and Visual Cognizance of Multivariate Temporal Tabular Data Using Machine Learning. 136–137. 1 indexed citations

6.

Majumdar, Arjun, Laura J. Brattain, Brian A. Telfer, Chad W. Farris, & Jonathan Scalera. (2018). Detecting Intracranial Hemorrhage with Deep Learning. PubMed. 2018. 583–587. 60 indexed citations

7.

Cha, Miriam, et al.. (2018). Improving Sar Automatic Target Recognition Using Simulated Images Under Deep Residual Refinements. 40 indexed citations

8.

Telfer, Brian A., Arjun Majumdar, Heejin Choi, et al.. (2018). Learning-based long-range axon tracing in dense scenes. 9. 1578–1582. 3 indexed citations

9.

Anderson, Christian N. K., et al.. (2015). A network science approach to open source data fusion and analytics for disaster response. International Conference on Information Fusion. 207–214. 4 indexed citations

10.

Anderson, Christian N. K., et al.. (2015). Application of graph methods for leveraging open source data during disaster response. 2. 259–266. 1 indexed citations

11.

Majumdar, Arjun, et al.. (2006). Classifying Infrastructure in an Urban Battlespace Using Thermal IR Signatures. Defense Technical Information Center (DTIC). 1 indexed citations

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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