Matthew J. Darr

1.6k total citations · 1 hit paper
63 papers, 1.2k citations indexed

About

Matthew J. Darr is a scholar working on Biomedical Engineering, Plant Science and Mechanics of Materials. According to data from OpenAlex, Matthew J. Darr has authored 63 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Biomedical Engineering, 15 papers in Plant Science and 14 papers in Mechanics of Materials. Recurrent topics in Matthew J. Darr's work include Biofuel production and bioconversion (17 papers), Soil Mechanics and Vehicle Dynamics (12 papers) and Forest Biomass Utilization and Management (12 papers). Matthew J. Darr is often cited by papers focused on Biofuel production and bioconversion (17 papers), Soil Mechanics and Vehicle Dynamics (12 papers) and Forest Biomass Utilization and Management (12 papers). Matthew J. Darr collaborates with scholars based in United States, India and Canada. Matthew J. Darr's co-authors include Ajay Shah, Dorde Medic, Jeffrey J. Zimmerman, Keith Webster, Lingying Zhao, Adam Thelen, Shawn Kenny, Sheng Shen, Venkat Pavan Nemani and Chao Hu and has published in prestigious journals such as Bioresource Technology, Fuel and Energy & Fuels.

In The Last Decade

Matthew J. Darr

61 papers receiving 1.1k citations

Hit Papers

A physics-informed deep learning approach for bearing fau... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew J. Darr United States 16 630 218 181 150 108 63 1.2k
Greg Schoenau Canada 24 621 1.0× 733 3.4× 261 1.4× 169 1.1× 192 1.8× 90 1.7k
Torsten Fransson Sweden 27 809 1.3× 901 4.1× 106 0.6× 125 0.8× 58 0.5× 210 2.5k
Wenyan Li China 24 408 0.6× 181 0.8× 41 0.2× 325 2.2× 138 1.3× 67 1.6k
Clara Serrano United Kingdom 13 506 0.8× 166 0.8× 79 0.4× 23 0.2× 51 0.5× 21 1.0k
S. Sokhansanj Canada 17 857 1.4× 304 1.4× 363 2.0× 16 0.1× 112 1.0× 62 1.4k
Kevin Kenney United States 13 1.1k 1.8× 182 0.8× 453 2.5× 41 0.3× 38 0.4× 29 1.5k
J. Morán Spain 18 924 1.5× 256 1.2× 103 0.6× 35 0.2× 25 0.2× 29 1.3k
Phani Adapa Canada 20 659 1.0× 298 1.4× 171 0.9× 13 0.1× 91 0.8× 35 1.1k
Subodh Kumar India 23 267 0.4× 265 1.2× 102 0.6× 23 0.2× 185 1.7× 57 1.3k
Zhaobing Liu China 25 330 0.5× 961 4.4× 704 3.9× 99 0.7× 98 0.9× 80 1.7k

Countries citing papers authored by Matthew J. Darr

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Darr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew J. Darr

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

All Works

20 of 20 papers shown
1.
Darr, Matthew J., et al.. (2025). Influence of Model Size and Image Augmentations on Object Detection in Low-Contrast Complex Background Scenes. AI. 6(3). 52–52. 2 indexed citations
2.
Smith, Benjamin C., et al.. (2023). Evaluation of Ultrasonic Sensor for Precision Liquid Volume Measurement in Narrow Tubes and Pipes. AgriEngineering. 5(1). 287–298. 2 indexed citations
3.
Darr, Matthew J., et al.. (2023). Optimized Chassis Stability Relative to Dynamic Terrain Profiles in a Self-Propelled Sprayer Multibody Dynamics Model. Journal of the ASABE. 66(1). 127–139. 1 indexed citations
4.
Darr, Matthew J., et al.. (2022). Validation Principles of Agricultural Machine Multibody Dynamics Models. Journal of the ASABE. 65(4). 801–814. 4 indexed citations
5.
Shen, Sheng, Hao Lü, Mohammadkazem Sadoughi, et al.. (2021). A physics-informed deep learning approach for bearing fault detection. Engineering Applications of Artificial Intelligence. 103. 104295–104295. 184 indexed citations breakdown →
6.
Shah, Ajay, Ashish Manandhar, & Matthew J. Darr. (2021). Near‐term practical strategies to improve the life cycle techno‐economics, energy use and greenhouse gas emissions of corn stover supply system for biobased industries. Biofuels Bioproducts and Biorefining. 15(3). 793–803. 2 indexed citations
7.
Darr, Matthew J., et al.. (2015). Understanding management practices for biomass harvest equipment for commercial scale operation. 2015 ASABE International Meeting. 2 indexed citations
8.
Pires, Alda F. A., et al.. (2013). Longitudinal study to evaluate the association between thermal environment and Salmonella shedding in a midwestern US swine farm. Preventive Veterinary Medicine. 112(1-2). 128–137. 7 indexed citations
10.
Shah, Ajay, Matthew J. Darr, Dustin L. Dalluge, et al.. (2012). Physicochemical properties of bio-oil and biochar produced by fast pyrolysis of stored single-pass corn stover and cobs. Bioresource Technology. 125. 348–352. 50 indexed citations
11.
Darr, Matthew J.. (2012). CAN Bus Technology Enables Advanced Machinery Management. Iowa State University Digital Repository (Iowa State University). 19(5). 10–11. 11 indexed citations
12.
Webster, K. E., et al.. (2012). Technical Note: Durability Analysis of Large Corn Stover Briquettes. Applied Engineering in Agriculture. 28(1). 9–14. 4 indexed citations
13.
Shah, Ajay, et al.. (2011). Techno‐economic analysis of a production‐scale torrefaction system for cellulosic biomass upgrading. Biofuels Bioproducts and Biorefining. 6(1). 45–57. 41 indexed citations
14.
Shah, Ajay, Matthew J. Darr, Keith Webster, & Christopher Hoffman. (2011). Outdoor Storage Characteristics of Single-Pass Large Square Corn Stover Bales in Iowa. Energies. 4(10). 1687–1695. 32 indexed citations
15.
Sharda, Ajay, John P. Fulton, Timothy McDonald, et al.. (2009). Real-Time Pressure and Flow Response for Swath Control Technology. 2009 Reno, Nevada, June 21 - June 24, 2009. 1 indexed citations
16.
Darr, Matthew J. & Lingying Zhao. (2008). Modeling Path Loss in Confined Animal Feeding Operations. 2008 Providence, Rhode Island, June 29 - July 2, 2008. 3 indexed citations
17.
McDonald, Timothy, et al.. (2008). Evaluation of a system to spatially monitor hand planting of pine seedlings. Computers and Electronics in Agriculture. 64(2). 173–182. 10 indexed citations
18.
Darr, Matthew J., Lingying Zhao, & Mohammad Reza Ehsani. (2007). Implementation of Controller Area Networks for Monitoring of Animal Environments. ASHRAE winter conference papers. 113(1). 2 indexed citations
19.
Darr, Matthew J., T. S. Stombaugh, S. A. Shearer, & Richard S. Gates. (2007). A New Course to Teach Microcontrollers and Embedded Networking to Biosystems and Agricultural Engineers. International journal of engineering education. 23(4). 716–722. 3 indexed citations
20.
Darr, Matthew J.. (2004). DEVELOPMENT AND EVALUATION OF A CONTROLLER AREA NETWORK BASED AUTONOMOUS VEHICLE. UKnowledge (University of Kentucky). 4 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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