J. Inglis

453 total citations
12 papers, 259 citations indexed

About

J. Inglis is a scholar working on Mathematical Physics, Statistical and Nonlinear Physics and Cognitive Neuroscience. According to data from OpenAlex, J. Inglis has authored 12 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Mathematical Physics, 5 papers in Statistical and Nonlinear Physics and 5 papers in Cognitive Neuroscience. Recurrent topics in J. Inglis's work include Neural dynamics and brain function (5 papers), stochastic dynamics and bifurcation (5 papers) and Advanced Thermodynamics and Statistical Mechanics (3 papers). J. Inglis is often cited by papers focused on Neural dynamics and brain function (5 papers), stochastic dynamics and bifurcation (5 papers) and Advanced Thermodynamics and Statistical Mechanics (3 papers). J. Inglis collaborates with scholars based in United Kingdom, France and United States. J. Inglis's co-authors include François Delarue, Étienne Tanré, Olivier Faugeras, Bogusław Zegarliński, Denis Talay and Vasilis Kontis and has published in prestigious journals such as Technometrics, Journal of Functional Analysis and Journal of Mathematical Biology.

In The Last Decade

J. Inglis

10 papers receiving 242 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Inglis United Kingdom	7	103	86	50	48	41	12	259
D. Easwaramoorthy India	9	88 0.9×	78 0.9×	51 1.0×	97 2.0×	4 0.1×	30	364
Stefano Galatolo Italy	15	238 2.3×	38 0.4×	58 1.2×	275 5.7×	57 1.4×	59	537
Avanti Athreya United States	7	126 1.2×	45 0.5×	88 1.8×	10 0.2×	14 0.3×	16	243
Martin V. Day United States	12	190 1.8×	11 0.1×	5 0.1×	101 2.1×	59 1.4×	34	374
Agnes Radl Germany	8	72 0.7×	5 0.1×	61 1.2×	59 1.2×	12 0.3×	15	218
Tzuu-Shuh Chiang Taiwan	6	24 0.2×	6 0.1×	88 1.8×	63 1.3×	27 0.7×	19	258
Mau-Hsiang Shih Taiwan	13	23 0.2×	19 0.2×	34 0.7×	58 1.2×	36 0.9×	50	518
Luciana De Micco Argentina	9	185 1.8×	43 0.5×	66 1.3×	23 0.5×	29 0.7×	29	334
Alejandro García del Amo Spain	9	185 1.8×	13 0.2×	41 0.8×	50 1.0×	53 1.3×	11	333
Anthony Quas United States	14	182 1.8×	5 0.1×	37 0.7×	351 7.3×	58 1.4×	56	485

Countries citing papers authored by J. Inglis

Since Specialization

Citations

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

Fields of papers citing papers by J. Inglis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Inglis

This figure shows the co-authorship network connecting the top 25 collaborators of J. Inglis. A scholar is included among the top collaborators of J. Inglis 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 J. Inglis. J. Inglis 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.

Inglis, J., et al.. (2016). A General Framework for Stochastic Traveling Waves and Patterns, with Application to Neural Field Equations. SIAM Journal on Applied Dynamical Systems. 15(1). 195–234. 25 indexed citations

2.

Delarue, François, et al.. (2015). Particle systems with a singular mean-field self-excitation. Application to neuronal networks. Stochastic Processes and their Applications. 125(6). 2451–2492. 50 indexed citations

3.

Delarue, François, et al.. (2015). Global solvability of a networked integrate-and-fire model of McKean–Vlasov type. The Annals of Applied Probability. 25(4). 57 indexed citations

4.

Inglis, J. & Denis Talay. (2015). Mean-Field Limit of a Stochastic Particle System Smoothly Interacting Through Threshold Hitting-Times and Applications to Neural Networks with Dendritic Component. SIAM Journal on Mathematical Analysis. 47(5). 3884–3916. 8 indexed citations

5.

Faugeras, Olivier & J. Inglis. (2014). Stochastic neural field equations: a rigorous footing. Journal of Mathematical Biology. 71(2). 259–300. 36 indexed citations

6.

Inglis, J., et al.. (2012). ERGODICITY FOR INFINITE PARTICLE SYSTEMS WITH LOCALLY CONSERVED QUANTITIES. Infinite Dimensional Analysis Quantum Probability and Related Topics. 15(1). 1250005–1250005. 6 indexed citations

7.

Inglis, J.. (2012). Spectral inequalities for operators on H-type groups. Journal of Spectral Theory. 2(1). 79–105. 2 indexed citations

8.

Inglis, J.. (2010). Coercive Inequalities for Generators of H¨ ormander Type. OpenGrey (Institut de l'Information Scientifique et Technique). 6 indexed citations

9.

Inglis, J., et al.. (2010). Liggett-type inequalities and interacting particle systems: The Gaussian case. 498–504. 1 indexed citations

10.

Inglis, J.. (2010). Operators on the Heisenberg group with discrete spectra. 491–497. 1 indexed citations

11.

Inglis, J., Vasilis Kontis, & Bogusław Zegarliński. (2010). From U-bounds to isoperimetry with applications to H-type groups. Journal of Functional Analysis. 260(1). 76–116. 12 indexed citations

12.

Inglis, J.. (1978). A Mathematical Theory of Evidence. Technometrics. 20(1). 106–106. 55 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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