Dylan Rankin

12.0k total citations
16 papers, 200 citations indexed

About

Dylan Rankin is a scholar working on Artificial Intelligence, Astronomy and Astrophysics and Nuclear and High Energy Physics. According to data from OpenAlex, Dylan Rankin has authored 16 papers receiving a total of 200 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Astronomy and Astrophysics and 5 papers in Nuclear and High Energy Physics. Recurrent topics in Dylan Rankin's work include Pulsars and Gravitational Waves Research (5 papers), Gamma-ray bursts and supernovae (5 papers) and Particle physics theoretical and experimental studies (4 papers). Dylan Rankin is often cited by papers focused on Pulsars and Gravitational Waves Research (5 papers), Gamma-ray bursts and supernovae (5 papers) and Particle physics theoretical and experimental studies (4 papers). Dylan Rankin collaborates with scholars based in United States, Switzerland and United Kingdom. Dylan Rankin's co-authors include Philip Harris, Vladimir Lončar, Z. Wu, Giuseppe Di Guglielmo, Duc Hoang, M. Pierini, J. Duarte, J. Ngadiuba, Silviu‐Marian Udrescu and T. F. Stratton and has published in prestigious journals such as Journal of High Energy Physics, Physical review. D and Classical and Quantum Gravity.

In The Last Decade

Dylan Rankin

16 papers receiving 187 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dylan Rankin United States	8	81	76	39	32	28	16	200
Philip Harris United States	9	226 2.8×	106 1.4×	40 1.0×	28 0.9×	39 1.4×	21	357
Ramon Winterhalder Germany	7	185 2.3×	73 1.0×	16 0.4×	13 0.4×	18 0.6×	11	233
S.‐C. Hsu United States	7	167 2.1×	64 0.8×	12 0.3×	12 0.4×	18 0.6×	33	229
A. Portas Spain	10	156 1.9×	36 0.5×	21 0.5×	11 0.3×	32 1.1×	40	262
I. Kisel Germany	9	238 2.9×	51 0.7×	11 0.3×	15 0.5×	9 0.3×	61	328
V. M. Mikuni United States	13	325 4.0×	166 2.2×	35 0.9×	19 0.6×	12 0.4×	27	420
Juan Pavez Chile	7	187 2.3×	118 1.6×	22 0.6×	36 1.1×	26 0.9×	14	314
Joshua Isaacson United States	12	438 5.4×	116 1.5×	16 0.4×	16 0.5×	21 0.8×	32	515
Sascha Diefenbacher Germany	10	252 3.1×	90 1.2×	39 1.0×	12 0.4×	22 0.8×	16	320
H. Qu China	6	273 3.4×	108 1.4×	21 0.5×	20 0.6×	13 0.5×	15	348

Countries citing papers authored by Dylan Rankin

Since Specialization

Citations

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

Fields of papers citing papers by Dylan Rankin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dylan Rankin

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

All Works

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16 of 16 papers shown

Rankin, Dylan, et al.. (2025). MACK: Mismodeling addressed with contrastive knowledge. SciPost Physics. 18(5). 1 indexed citations

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

Tsoi, Ho Fung, Dylan Rankin, C. Caillol, et al.. (2025). SymbolFit: Automatic Parametric Modeling with Symbolic Regression. CERN Document Server (European Organization for Nuclear Research). 9(1). 2 indexed citations

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

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

Khoda, E. E., Dylan Rankin, R. Teixeira De Lima, et al.. (2023). Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. Machine Learning Science and Technology. 4(2). 25004–25004. 8 indexed citations

Rankin, Dylan, Philip Harris, E. Katsavounidis, et al.. (2022). A Software Ecosystem for Deploying Deep Learning in Gravitational Wave Physics. 9–17. 3 indexed citations

Rankin, Dylan, J. Krupa, M. Saleem, et al.. (2022). Hardware-accelerated inference for real-time gravitational-wave astronomy. Nature Astronomy. 6(5). 529–536. 12 indexed citations

Tarafdar, Naif, Giuseppe Di Guglielmo, Philip Harris, et al.. (2021). AIgean : An Open Framework for Deploying Machine Learning on Heterogeneous Clusters. ACM Transactions on Reconfigurable Technology and Systems. 15(3). 1–32. 7 indexed citations

10.

Rankin, Dylan, et al.. (2021). Quasi anomalous knowledge: searching for new physics with embedded knowledge. Journal of High Energy Physics. 2021(6). 25 indexed citations

11.

Ngadiuba, J., Vladimir Lončar, M. Pierini, et al.. (2020). Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML. DSpace@MIT (Massachusetts Institute of Technology). 44 indexed citations

12.

Guglielmo, Giuseppe Di, J. Duarte, P. Harris, et al.. (2020). Fast inference of Boosted Decision Trees in FPGAs for particle physics. Journal of Instrumentation. 15(5). P05026–P05026. 50 indexed citations

13.

Tarafdar, Naif, Giuseppe Di Guglielmo, Philip Harris, et al.. (2020). AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters. CERN Document Server (European Organization for Nuclear Research). 239–239. 4 indexed citations

14.

Duarte, J., Song Han, Philip Harris, et al.. (2019). Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. 305–305. 5 indexed citations

15.

Brown, Robert D., et al.. (1954). Elastic Scattering of Deuterons byHe3. Physical Review. 96(1). 80–82. 12 indexed citations

16.

Stratton, William, George D. Freier, G.R. Keepin, Dylan Rankin, & T. F. Stratton. (1952). The Elastic Scattering of Deuterons by Tritons. Physical Review. 88(2). 257–261. 12 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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