Joshua Bongard

524 total citations
12 papers, 285 citations indexed

About

Joshua Bongard is a scholar working on Artificial Intelligence, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Joshua Bongard has authored 12 papers receiving a total of 285 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Molecular Biology and 3 papers in Cognitive Neuroscience. Recurrent topics in Joshua Bongard's work include Evolutionary Algorithms and Applications (6 papers), Gene Regulatory Network Analysis (3 papers) and Reinforcement Learning in Robotics (3 papers). Joshua Bongard is often cited by papers focused on Evolutionary Algorithms and Applications (6 papers), Gene Regulatory Network Analysis (3 papers) and Reinforcement Learning in Robotics (3 papers). Joshua Bongard collaborates with scholars based in United States. Joshua Bongard's co-authors include Michael Levin, Douglas Blackiston, Simon Garnier, Sam Kriegman, Joshua E. Auerbach, John H. Long, David Wallach, Douglas Moore, Thomas F. Varley and Sara Imari Walker and has published in prestigious journals such as PLoS Computational Biology, Science Robotics and Frontiers in Ecology and Evolution.

In The Last Decade

Joshua Bongard

11 papers receiving 277 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joshua Bongard United States	6	87	65	60	55	54	12	285
Michał Joachimczak Japan	10	120 1.4×	50 0.8×	81 1.4×	21 0.4×	48 0.9×	30	237
Takayuki Niizato Japan	11	36 0.4×	67 1.0×	11 0.2×	50 0.9×	95 1.8×	35	335
Taras Kowaliw France	8	105 1.2×	37 0.6×	46 0.8×	19 0.3×	19 0.4×	25	188
Olivier Michel France	9	52 0.6×	137 2.1×	90 1.5×	8 0.1×	67 1.2×	22	286
Jason W. Rocks United States	8	27 0.3×	85 1.3×	61 1.0×	29 0.5×	79 1.5×	17	310
Jan Frederik Totz Germany	9	22 0.3×	64 1.0×	28 0.5×	91 1.7×	130 2.4×	16	407
Yuta Nishiyama Japan	9	24 0.3×	61 0.9×	9 0.1×	38 0.7×	28 0.5×	35	320
Joshua P. Hecker United States	9	38 0.4×	98 1.5×	112 1.9×	9 0.2×	32 0.6×	23	268
Ivica Slavkov Slovenia	6	53 0.6×	51 0.8×	94 1.6×	11 0.2×	31 0.6×	9	209
Nathanaël Aubert-Kato Japan	9	37 0.4×	131 2.0×	31 0.5×	14 0.3×	84 1.6×	26	257

Countries citing papers authored by Joshua Bongard

Since Specialization

Citations

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

Fields of papers citing papers by Joshua Bongard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joshua Bongard

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

All Works

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12 of 12 papers shown

1.

Blackiston, Douglas, Thomas F. Varley, Douglas Moore, et al.. (2025). Revealing non-trivial information structures in aneural biological tissues via functional connectivity. PLoS Computational Biology. 21(4). e1012149–e1012149. 4 indexed citations

2.

Bongard, Joshua & Michael Levin. (2023). There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines. Biomimetics. 8(1). 110–110. 25 indexed citations

3.

Blackiston, Douglas, et al.. (2021). A cellular platform for the development of synthetic living machines. Science Robotics. 6(52). 110 indexed citations

4.

Bongard, Joshua & Michael Levin. (2021). Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior. Frontiers in Ecology and Evolution. 9. 53 indexed citations

5.

Bongard, Joshua, et al.. (2017). Epigenetic Operators and the Evolution of Physically Embodied Robots. Frontiers in Robotics and AI. 4. 5 indexed citations

6.

Livingston, Kenneth R., Marc L. Smith, Jodi Schwarz, et al.. (2016). Modularity and Sparsity: Evolution of Neural Net Controllers in Physically Embodied Robots. Frontiers in Robotics and AI. 3. 3 indexed citations

7.

Bongard, Joshua, et al.. (2015). Exploiting the Relationship Between Structural Modularity and Sparsity for Faster Network Evolution. 1173–1176. 4 indexed citations

8.

Bongard, Joshua, et al.. (2014). Collective Design of Robot Locomotion. 138–145. 1 indexed citations

9.

Bongard, Joshua, et al.. (2014). Collective Design of Robot Locomotion. 138–145. 5 indexed citations

10.

Bongard, Joshua, et al.. (2013). Improving genetic programming based symbolic regression using deterministic machine learning. 1763–1770. 44 indexed citations

11.

Bongard, Joshua, et al.. (2013). Modeling hierarchy using symbolic regression. 2980–2987.

12.

Auerbach, Joshua E. & Joshua Bongard. (2012). On the relationship between environmental and morphological complexity in evolved robots. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 521–528. 31 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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