Joshua Garland

986 total citations
31 papers, 549 citations indexed

About

Joshua Garland is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Economics and Econometrics. According to data from OpenAlex, Joshua Garland has authored 31 papers receiving a total of 549 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Statistical and Nonlinear Physics and 7 papers in Economics and Econometrics. Recurrent topics in Joshua Garland's work include Complex Systems and Time Series Analysis (7 papers), Time Series Analysis and Forecasting (5 papers) and Neural dynamics and brain function (4 papers). Joshua Garland is often cited by papers focused on Complex Systems and Time Series Analysis (7 papers), Time Series Analysis and Forecasting (5 papers) and Neural dynamics and brain function (4 papers). Joshua Garland collaborates with scholars based in United States, Switzerland and United Kingdom. Joshua Garland's co-authors include Elizabeth Bradley, Paul A. Baker, Ryan G. James, E. J. Ekdahl, James D. Meiss, Elisa Omodei, Elizabeth A. Hobson, Tyler R. Jones, James W. C. White and Artemy Kolchinsky and has published in prestigious journals such as Nature, PLoS ONE and The American Naturalist.

In The Last Decade

Joshua Garland

29 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joshua Garland United States	13	128	87	86	81	69	31	549
Murray Jorgensen New Zealand	11	95 0.7×	71 0.8×	123 1.4×	42 0.5×	67 1.0×	26	697
Annette Witt Germany	15	212 1.7×	178 2.0×	74 0.9×	93 1.1×	130 1.9×	26	824
Luis J. Gilarranz Switzerland	14	49 0.4×	61 0.7×	49 0.6×	282 3.5×	227 3.3×	20	961
Deniz Eroglu Türkiye	13	148 1.2×	201 2.3×	140 1.6×	25 0.3×	86 1.2×	26	551
Vyacheslav Lyubchich United States	16	38 0.3×	34 0.4×	36 0.4×	127 1.6×	151 2.2×	47	602
Thomas Stemler Australia	15	104 0.8×	263 3.0×	207 2.4×	22 0.3×	80 1.2×	50	630
M. M. Dodson United Kingdom	14	23 0.2×	127 1.5×	28 0.3×	185 2.3×	114 1.7×	58	1.1k
Nishant Malik United States	12	213 1.7×	108 1.2×	98 1.1×	12 0.1×	318 4.6×	25	548
Clifford T. Brown United States	12	25 0.2×	39 0.4×	37 0.4×	44 0.5×	27 0.4×	14	633
G. Morein United States	6	99 0.8×	73 0.8×	103 1.2×	60 0.7×	263 3.8×	8	590

Countries citing papers authored by Joshua Garland

Since Specialization

Citations

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

Fields of papers citing papers by Joshua Garland

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joshua Garland

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Hébert‐Dufresne, Laurent, Antoine Allard, Joshua Garland, Elizabeth A. Hobson, & Luis Zaman. (2024). The path of complexity. 1(1). 9 indexed citations

Bhattacharjee, Amrita, Raha Moraffah, Joshua Garland, & Huan Liu. (2024). Zero-shot LLM-guided Counterfactual Generation: A Case Study on NLP Model Evaluation. 1243–1248. 5 indexed citations

Bhattacharjee, Amrita, James H. Cook, Matthias Kirchner, et al.. (2024). Defending Against Social Engineering Attacks in the Age of LLMs. 12880–12902. 6 indexed citations

Bradley, Elizabeth, James W. C. White, & Joshua Garland. (2024). Thoughtful data analysis. Chaos An Interdisciplinary Journal of Nonlinear Science. 34(10).

Bhattacharjee, Amrita, et al.. (2023). J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News. 484–497. 1 indexed citations

Moraffah, Raha, et al.. (2023). How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts. 1337–1349. 4 indexed citations

Meikle, R. D., et al.. (2023). Using scaling-region distributions to select embedding parameters. Physica D Nonlinear Phenomena. 446. 133674–133674. 4 indexed citations

Garland, Joshua, et al.. (2023). Correction: Impact and dynamics of hate and counter speech online. EPJ Data Science. 12(1). 1 indexed citations

Kao, Albert B., Amanda K. Hund, Fernando P. Santos, et al.. (2023). Opposing Responses to Scarcity Emerge from Functionally Unique Sociality Drivers. The American Naturalist. 202(3). 302–321. 2 indexed citations

10.

Bradley, Elizabeth, et al.. (2021). Detection of local mixing in time-series data using permutation entropy. Physical review. E. 103(2). 22217–22217. 2 indexed citations

11.

Pennekamp, Frank, Alison C. Iles, Joshua Garland, et al.. (2019). The intrinsic predictability of ecological time series and its potential to guide forecasting. Ecological Monographs. 89(2). 84 indexed citations

12.

Pruitt, Jonathan N., Andrew M. Berdahl, Christina Riehl, et al.. (2018). Social tipping points in animal societies. Proceedings of the Royal Society B Biological Sciences. 285(1887). 20181282–20181282. 27 indexed citations

13.

Garland, Joshua, et al.. (2018). Anomaly Detection in Paleoclimate Records Using Permutation Entropy. Entropy. 20(12). 931–931. 30 indexed citations

14.

Tao, Susumu, Samuel F. Way, Joshua Garland, et al.. (2017). Ablation as targeted perturbation to rewire communication network of persistent atrial fibrillation. PLoS ONE. 12(7). e0179459–e0179459. 13 indexed citations

15.

Garland, Joshua, Ryan G. James, & Elizabeth Bradley. (2016). Leveraging information storage to select forecast-optimal parameters for delay-coordinate reconstructions. Physical review. E. 93(2). 22221–22221. 23 indexed citations

16.

Ashikaga, Hiroshi, José Aguilar-Rodríguez, Elizabeth R. Lusczek, et al.. (2015). Modelling the heart as a communication system. Journal of The Royal Society Interface. 12(105). 20141201–20141201. 9 indexed citations

17.

Omodei, Elisa, et al.. (2015). Followers Are Not Enough: A Multifaceted Approach to Community Detection in Online Social Networks. PLoS ONE. 10(8). e0134860–e0134860. 30 indexed citations

18.

Garland, Joshua, Ryan G. James, & Elizabeth Bradley. (2014). Quantifying Time-Series Predictability through Structural Complexity.. arXiv (Cornell University). 1 indexed citations

19.

Garland, Joshua, Ryan G. James, & Elizabeth Bradley. (2014). Model-free quantification of time-series predictability. Physical Review E. 90(5). 52910–52910. 54 indexed citations

20.

Baker, Paul A., et al.. (2005). Holocene hydrologic variation at Lake Titicaca, Bolivia/Peru, and its relationship to North Atlantic climate variation. Journal of Quaternary Science. 20(7-8). 655–662. 92 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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