Subhadeep Paul
Impact in
- Computational Mathematics top 10%
- Ecology top 10%
- Bacteriophages and microbial interactions
- Microbial Community Ecology and Physiology
Papers in
-
- Complex Network Analysis Techniques 5
- Opinion Dynamics and Social Influence 2
-
- Mental Health Research Topics 3
- Co-authors
- Yuguo Chen (4 shared papers)Tijana Glavina del Rio (2 shared papers)Cristina Howard‐Varona (2 shared papers)Bill Andreopoulos (1 shared paper)Natalie Solonenko (2 shared papers)Joshua Adkins (2 shared papers)Ahmed A. Zayed (2 shared papers)Melissa B. Duhaime (2 shared papers)
- Journals
- The ISME Journal (2 papers)The Annals of Applied Statistics (2 papers)Frontiers in Neuroscience (1 paper)Electronic Journal of Statistics (1 paper)The Annals of Statistics (1 paper)
- Partner nations
- United States
In The Last Decade
Subhadeep Paul
9 papers receiving 270 citations
Peers
Comparison fields: 5 of 61
- Computational Mathematics 9
- Ecology 151
- Statistical and Nonlinear Physics 59
- Sensory Systems 16
- Endocrinology 17
Countries citing papers authored by Subhadeep Paul
This map shows the geographic impact of Subhadeep Paul'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 Subhadeep Paul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subhadeep Paul more than expected).
Fields of papers citing papers by Subhadeep Paul
This network shows the impact of papers produced by Subhadeep Paul. 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 Subhadeep Paul. The network helps show where Subhadeep Paul may publish in the future.
Co-authors
The 25 scholars most cited alongside Subhadeep Paul, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 153 | |
| 2 | 2020 | 47 | |
| 3 | 2019 | 23 | |
| 4 | 2020 | 12 | |
| 5 | 2021 | 12 | |
| 6 | 2024 | 11 | |
| 7 | 2021 | 8 | |
| 8 | 2023 | 3 | |
| 9 | EFFECT OF AUTOMATED BURNER KNOB FOR DIFFERENT MEDIUM ON GASCONSUMPTION BY LOCAL STOVE FOR HOUSEHOLD AND INDUSTRIALSAFETY | 2017 | 1 |
| 10 | 2024 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 |
About Subhadeep Paul
Subhadeep Paul is a scholar working on Statistical and Nonlinear Physics, Experimental and Cognitive Psychology, Molecular Biology, Ecology and Automotive Engineering, having authored 12 papers that have together received 270 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Mental Health Research Topics (3 papers), Bioinformatics and Genomic Networks (2 papers), Bacteriophages and microbial interactions (2 papers), Opinion Dynamics and Social Influence (2 papers), Energy and Environment Impacts (1 paper), Advanced Battery Technologies Research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Computational Mathematics (9 citations), Ecology (151 citations), Statistical and Nonlinear Physics (59 citations), Sensory Systems (16 citations) and Endocrinology (17 citations). Subhadeep Paul has collaborated with scholars based in United States. Frequent co-authors include Yuguo Chen, Tijana Glavina del Rio, Cristina Howard‐Varona, Bill Andreopoulos, Natalie Solonenko, Joshua Adkins, Ahmed A. Zayed, Melissa B. Duhaime, Ho Bin Jang and Matthew B. Sullivan. Their work appears in journals such as The ISME Journal, The Annals of Applied Statistics, Frontiers in Neuroscience, Electronic Journal of Statistics and The Annals of Statistics.
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.