Subhro Das

788 citations
40 papers · 461 · h-index 10

Impact in

Papers in

Subhro Das

35 papers receiving 448 citations

Peers

Subhro Das
Comparison fields: 5 of 67
  • Computer Networks and Communications 213
  • Artificial Intelligence 213
  • Control and Systems Engineering 93
  • Electrical and Electronic Engineering 135
  • Mechanical Engineering 72
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Citations per field
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Citations per year

Countries citing papers authored by Subhro Das

Since Specialization
Citations

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

Fields of papers citing papers by Subhro Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015115
2 2016115
3 200637
4 200624
5 201319
6 200619
7 202315
8 202115
9 200515
10 201813
11 20058
12 20058
13 20236
14
Making Sense of Patient-Generated Health Data for Interpretable Patient-Centered Care: The Transition from "More" to "Better".
20176
15 20245
16 20135
17 20134
18 20214
19 20173
20
Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records.
20183

About Subhro Das

Subhro Das is a scholar working on Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Control and Systems Engineering and Mechanical Engineering, having authored 40 papers that have together received 461 indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (7 papers), Target Tracking and Data Fusion in Sensor Networks (7 papers), Electric Motor Design and Analysis (6 papers), Innovative Energy Harvesting Technologies (4 papers), Neural Networks Stability and Synchronization (3 papers), Machine Learning in Healthcare (3 papers), Distributed Sensor Networks and Detection Algorithms (3 papers) and Induction Heating and Inverter Technology (2 papers). The work is most often cited by research in Computer Networks and Communications (213 citations), Artificial Intelligence (213 citations), Control and Systems Engineering (93 citations), Electrical and Electronic Engineering (135 citations) and Mechanical Engineering (72 citations). Subhro Das has collaborated with scholars based in United States, India and Hong Kong. Frequent co-authors include José M. F. Moura, Mark G. Allen, David P. Arnold, Jeffrey H. Lang, I. Zana, Jung-Wook Park, Yingying Li, Na Li, Gregory W. Wornell and Prasanna Sattigeri. Their work appears in journals such as Journal of Microelectromechanical Systems, IEEE Transactions on Signal Processing, IEEE Journal of Biomedical and Health Informatics, International Journal of Emerging Electric Power Systems and IFAC-PapersOnLine.

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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