Deep Chatterjee

45.2k total citations
17 papers, 161 citations indexed

About

Deep Chatterjee is a scholar working on Astronomy and Astrophysics, Geophysics and Instrumentation. According to data from OpenAlex, Deep Chatterjee has authored 17 papers receiving a total of 161 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Astronomy and Astrophysics, 3 papers in Geophysics and 2 papers in Instrumentation. Recurrent topics in Deep Chatterjee's work include Gamma-ray bursts and supernovae (14 papers), Pulsars and Gravitational Waves Research (12 papers) and Cosmology and Gravitation Theories (4 papers). Deep Chatterjee is often cited by papers focused on Gamma-ray bursts and supernovae (14 papers), Pulsars and Gravitational Waves Research (12 papers) and Cosmology and Gravitation Theories (4 papers). Deep Chatterjee collaborates with scholars based in United States, India and Canada. Deep Chatterjee's co-authors include S. J. Kapadia, Nicolás Yunes, Kent Yagi, G. P. Holder, D. E. Holz, Scott Perkins, M. W. Coughlin, P. R. Brady, Gautham Narayan and Shaon Ghosh and has published in prestigious journals such as The Journal of Chemical Physics, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Deep Chatterjee

15 papers receiving 141 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deep Chatterjee United States 8 146 44 19 17 15 17 161
R. M. Magee United States 7 144 1.0× 41 0.9× 13 0.7× 12 0.7× 21 1.4× 10 153
Banafsheh Beheshtipour United States 7 128 0.9× 40 0.9× 19 1.0× 17 1.0× 22 1.5× 11 141
Jinchen Jiang China 8 180 1.2× 33 0.8× 7 0.4× 11 0.6× 17 1.1× 18 194
B. Miller Netherlands 4 74 0.5× 19 0.4× 23 1.2× 14 0.8× 7 0.5× 6 102
Alberto Mangiagli France 9 202 1.4× 50 1.1× 11 0.6× 6 0.4× 6 0.4× 11 212
H. Inchauspé Germany 5 92 0.6× 28 0.6× 8 0.4× 23 1.4× 4 0.3× 7 111
F. Morawski Poland 6 85 0.6× 22 0.5× 12 0.6× 28 1.6× 24 1.6× 8 101
M. Saleem United States 9 161 1.1× 40 0.9× 12 0.6× 13 0.8× 15 1.0× 19 179
V. Re Italy 5 119 0.8× 36 0.8× 5 0.3× 14 0.8× 21 1.4× 6 121
Sarah Caudill Netherlands 8 135 0.9× 13 0.3× 33 1.7× 18 1.1× 30 2.0× 14 150

Countries citing papers authored by Deep Chatterjee

Since Specialization
Citations

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

Fields of papers citing papers by Deep Chatterjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deep Chatterjee

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

All Works

17 of 17 papers shown
1.
Toivonen, Andrew, Sushant Sharma Chaudhary, S. Antier, et al.. (2025). What to Expect: Kilonova Light Curve Predictions via Equation of State Marginalization. Publications of the Astronomical Society of the Pacific. 137(3). 34506–34506.
2.
Benoit, William, Deep Chatterjee, M. Saleem, et al.. (2025). Machine-learning pipeline for real-time detection of gravitational waves from compact binary coalescences. Physical review. D. 111(4). 5 indexed citations
3.
Chatterjee, Deep, et al.. (2025). Rapid parameter estimation for kilonovae using likelihood-free inference. Monthly Notices of the Royal Astronomical Society. 541(3). 2619–2630.
4.
Govorkova, Ekaterina, William Benoit, Deep Chatterjee, et al.. (2024). GWAK: gravitational-wave anomalous knowledge with recurrent autoencoders. Machine Learning Science and Technology. 5(2). 25020–25020. 8 indexed citations
5.
Chatterjee, Deep, et al.. (2024). Neural post-Einsteinian framework for efficient theory-agnostic tests of general relativity with gravitational waves. Physical review. D. 110(2). 2 indexed citations
6.
Saleem, M., S.-W. Yeh, R. M. Magee, et al.. (2024). Demonstration of machine learning-assisted low-latency noise regression in gravitational wave detectors. Classical and Quantum Gravity. 41(19). 195024–195024. 2 indexed citations
7.
Chatterjee, Deep, et al.. (2024). Rapid likelihood free inference of compact binary coalescences using accelerated hardware. Machine Learning Science and Technology. 5(4). 45030–45030. 5 indexed citations
8.
Lokken, Martine, Alexander Gagliano, Gautham Narayan, et al.. (2023). The simulated catalogue of optical transients and correlated hosts (SCOTCH). Monthly Notices of the Royal Astronomical Society. 520(2). 2887–2912. 10 indexed citations
9.
Chatterjee, Deep, G. P. Holder, D. E. Holz, et al.. (2023). Breaking bad degeneracies with Love relations: Improving gravitational-wave measurements through universal relations. Physical review. D. 107(4). 10 indexed citations
10.
Narayan, Gautham, et al.. (2023). Predictions for electromagnetic counterparts to Neutron Star mergers discovered during LIGO-Virgo-KAGRA observing runs 4 and 5. Monthly Notices of the Royal Astronomical Society. 528(2). 1109–1124. 5 indexed citations
11.
Chatterjee, Deep, G. P. Holder, D. E. Holz, et al.. (2021). Cosmology with Love: Measuring the Hubble constant using neutron star universal relations. arXiv (Cornell University). 32 indexed citations
12.
Chatterjee, Deep, Gautham Narayan, P. Aleo, Konstantin Malanchev, & Daniel Muthukrishna. (2021). El-CID: A filter for Gravitational-wave Electromagnetic Counterpart Identification. arXiv (Cornell University). 8 indexed citations
13.
Singh, M. K., S. J. Kapadia, Md Arif Shaikh, Deep Chatterjee, & P. Ajith. (2021). Improved early warning of compact binary mergers using higher modes of gravitational radiation: a population study. Monthly Notices of the Royal Astronomical Society. 502(2). 1612–1622. 9 indexed citations
14.
Chatterjee, Deep, P. R. Brady, S. J. Kapadia, et al.. (2020). A Machine Learning-based Source Property Inference for Compact Binary Mergers. The Astrophysical Journal. 896(1). 54–54. 24 indexed citations
15.
Chatterjee, Deep, P. Nugent, P. R. Brady, et al.. (2019). Toward Rate Estimation for Transient Surveys. I. Assessing Transient Detectability and Volume Sensitivity for iPTF. The Astrophysical Journal. 881(2). 128–128. 2 indexed citations
16.
Coughlin, M. W., M. Chan, Deep Chatterjee, et al.. (2018). Optimizing searches for electromagnetic counterparts of gravitational wave triggers. Monthly Notices of the Royal Astronomical Society. 478(1). 692–702. 37 indexed citations
17.
Chatterjee, Deep, Srabanti Chaudhury, & Binny J. Cherayil. (2007). The dynamics of intermittent strand separation in double-stranded DNA. The Journal of Chemical Physics. 127(15). 155104–155104. 2 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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