J. Darby Smith

986 total citations
40 papers, 650 citations indexed

About

J. Darby Smith is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Safety, Risk, Reliability and Quality. According to data from OpenAlex, J. Darby Smith has authored 40 papers receiving a total of 650 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Electrical and Electronic Engineering, 16 papers in Artificial Intelligence and 7 papers in Safety, Risk, Reliability and Quality. Recurrent topics in J. Darby Smith's work include Advanced Memory and Neural Computing (15 papers), Ferroelectric and Negative Capacitance Devices (13 papers) and Traffic and Road Safety (7 papers). J. Darby Smith is often cited by papers focused on Advanced Memory and Neural Computing (15 papers), Ferroelectric and Negative Capacitance Devices (13 papers) and Traffic and Road Safety (7 papers). J. Darby Smith collaborates with scholars based in United States, Australia and Sweden. J. Darby Smith's co-authors include Wassim G Najm, Burak Sen, John Brewer, James B. Aimone, Suma Cardwell, Catherine D. Schuman, David L. Smith, Andrew D. Kent, Shashank Misra and Jean Anne C. Incorvia and has published in prestigious journals such as Advanced Materials, Journal of the American Statistical Association and Applied Physics Letters.

In The Last Decade

J. Darby Smith

31 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
J. Darby Smith United States	13	264	261	190	144	139	40	650
Najah AbuAli United Arab Emirates	14	56 0.2×	148 0.6×	340 1.8×	31 0.2×	59 0.4×	46	663
Sei-Wang Chen Taiwan	13	67 0.3×	153 0.6×	53 0.3×	37 0.3×	32 0.2×	38	489
Shunsuke Aoki Japan	12	16 0.1×	209 0.8×	181 1.0×	25 0.2×	171 1.2×	49	522
Javier Echanobe Spain	15	15 0.1×	117 0.4×	110 0.6×	22 0.2×	117 0.8×	48	552
T. J. Mateo Sanguino Spain	11	29 0.1×	57 0.2×	92 0.5×	20 0.1×	77 0.6×	58	477
Marcus Johnson United States	13	34 0.1×	106 0.4×	64 0.3×	62 0.4×	225 1.6×	35	721
Qi Deng Germany	8	51 0.2×	133 0.5×	21 0.1×	39 0.3×	172 1.2×	23	372
Francesco Zanlungo Japan	14	261 1.0×	83 0.3×	12 0.1×	170 1.2×	218 1.6×	37	865
S.S. Awad United States	12	19 0.1×	76 0.3×	293 1.5×	18 0.1×	77 0.6×	37	485

Countries citing papers authored by J. Darby Smith

Since Specialization

Citations

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

Fields of papers citing papers by J. Darby Smith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Darby Smith

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

Cardwell, Suma, J. Darby Smith, Samuel Liu, et al.. (2025). AI-Guided Codesign for Novel Computing Paradigms. 849–856.

Smith, J. Darby, et al.. (2025). AI-guided framework for the design of materials and devices for magnetic-tunnel-junction-based true random number generators. Communications Engineering. 4(1). 43–43.

Smith, J. Darby, et al.. (2025). High-speed tunable generation of random number distributions using actuated perpendicular magnetic tunnel junctions. Applied Physics Letters. 126(21). 2 indexed citations

Misra, Shashank, et al.. (2025). Advantages of imperfect dice rolls over coin flips for random number generation. Scientific Reports. 15(1). 11818–11818.

Liu, Samuel, J. Darby Smith, James B. Aimone, et al.. (2024). Magnetic tunnel junction random number generators applied to dynamically tuned probability trees driven by spin orbit torque. Nanotechnology. 35(27). 275204–275204. 5 indexed citations

Misra, Shashank, et al.. (2023). Stochastic Magnetic Actuated Random Transducer Devices Based on Perpendicular Magnetic Tunnel Junctions. Physical Review Applied. 19(2). 18 indexed citations

Misra, Shashank, L. C. Bland, Suma Cardwell, et al.. (2023). Probabilistic Neural Computing with Stochastic Devices (Adv. Mater. 37/2023). Advanced Materials. 35(37). 4 indexed citations

Aimone, James B., Prasanna Date, G. A. Fonseca Guerra, et al.. (2022). A review of non-cognitive applications for neuromorphic computing. Neuromorphic Computing and Engineering. 2(3). 32003–32003. 33 indexed citations

Misra, Shashank, L. C. Bland, Suma Cardwell, et al.. (2022). Probabilistic Neural Computing with Stochastic Devices. Advanced Materials. 35(37). e2204569–e2204569. 55 indexed citations

10.

Liu, Samuel, Suma Cardwell, Catherine D. Schuman, et al.. (2022). Random Bitstream Generation Using Voltage-Controlled Magnetic Anisotropy and Spin Orbit Torque Magnetic Tunnel Junctions. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 8(2). 194–202. 16 indexed citations

11.

Cardwell, Suma, Catherine D. Schuman, J. Darby Smith, et al.. (2022). Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

12.

Aimone, James B., Richard B. Lehoucq, William Severa, & J. Darby Smith. (2021). Assessing a Neuromorphic Platform for use in Scientific Stochastic Sampling. 27. 64–73. 4 indexed citations

13.

Smith, J. Darby & Scott A. McKinley. (2018). Assessing the Impact of Electrostatic Drag on Processive Molecular Motor Transport. Bulletin of Mathematical Biology. 80(8). 2088–2123. 4 indexed citations

14.

Smith, J. Darby, et al.. (2014). Heavy Truck Pre-Crash Scenarios for Safety Applications Based on Vehicle-to-Vehicle Communications. 2 indexed citations

15.

Najm, Wassim G, et al.. (2013). Description of Light-Vehicle Pre-Crash Scenarios for Safety Applications Based on Vehicle-to-Vehicle Communications. 30 indexed citations

16.

Najm, Wassim G, et al.. (2003). Analysis of Light Vehicle Crashes and Pre-Crash Scenarios Based on the 2000 General Estimates System. Rosa P: A digital library for transportation research (United States Department of Transportation). 61 indexed citations

17.

Sen, Burak, J. Darby Smith, & Wassim G Najm. (2003). ANALYSIS OF LANE CHANGE CRASHES. 64 indexed citations

18.

Najm, Wassim G & J. Darby Smith. (2002). Breakdown of Light Vehicle Crashes by Pre-Crash Scenarios as a Basis for Countermeasure Development. 712–719. 6 indexed citations

19.

Tickle, Kevin S., et al.. (1997). A Bayesian Formulation of the Kalman Filter Applied to the Estimation of Individual Pharmacokinetic Parameters. Computers and Biomedical Research. 30(2). 83–94. 3 indexed citations

20.

Smith, J. Darby. (1985). PEDESTRIANISATION--SHOPPING STREETS IN SCOTLAND. 71(5).

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.

Explore authors with similar magnitude of impact