Mohammad Fard

2.1k total citations
94 papers, 1.3k citations indexed

About

Mohammad Fard is a scholar working on Automotive Engineering, Civil and Structural Engineering and Orthopedics and Sports Medicine. According to data from OpenAlex, Mohammad Fard has authored 94 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Automotive Engineering, 34 papers in Civil and Structural Engineering and 30 papers in Orthopedics and Sports Medicine. Recurrent topics in Mohammad Fard's work include Effects of Vibration on Health (27 papers), Vehicle Noise and Vibration Control (27 papers) and Acoustic Wave Phenomena Research (17 papers). Mohammad Fard is often cited by papers focused on Effects of Vibration on Health (27 papers), Vehicle Noise and Vibration Control (27 papers) and Acoustic Wave Phenomena Research (17 papers). Mohammad Fard collaborates with scholars based in Australia, Japan and China. Mohammad Fard's co-authors include Jiaxing Zhan, John L. Davy, Reza N. Jazar, Zhengqing Liu, Milad Abbasi, A. Ghafarinazari, Hormoz Marzbani, Mahdi Bodaghi, Bernard Rolfe and Stephen R. Robinson and has published in prestigious journals such as The Journal of the Acoustical Society of America, Journal of Sound and Vibration and Sustainability.

In The Last Decade

Mohammad Fard

87 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Fard Australia 21 578 420 405 312 202 94 1.3k
Mohammad Hosseini Fouladi Malaysia 14 235 0.4× 650 1.5× 361 0.9× 114 0.4× 71 0.4× 54 1.2k
Mohd Zaki Nuawi Malaysia 18 867 1.5× 453 1.1× 108 0.3× 324 1.0× 46 0.2× 170 1.5k
Zaidi Mohd Ripin Malaysia 20 731 1.3× 318 0.8× 211 0.5× 138 0.4× 53 0.3× 113 1.3k
Olivier Doutres Canada 20 160 0.3× 820 2.0× 158 0.4× 193 0.6× 29 0.1× 97 1.2k
A. M. R. Ribeiro Portugal 19 449 0.8× 278 0.7× 427 1.1× 553 1.8× 15 0.1× 54 1.2k
P.-É. Boileau Canada 20 142 0.2× 187 0.4× 289 0.7× 473 1.5× 695 3.4× 44 1.4k
Nobutaka TSUJIUCHI Japan 13 274 0.5× 471 1.1× 115 0.3× 131 0.4× 12 0.1× 188 807
Lapo Governi Italy 19 189 0.3× 306 0.7× 171 0.4× 71 0.2× 53 0.3× 112 1.3k
Zhonghao Bai China 23 890 1.5× 152 0.4× 558 1.4× 400 1.3× 12 0.1× 68 1.7k
A.N. Thite United Kingdom 12 258 0.4× 221 0.5× 284 0.7× 445 1.4× 13 0.1× 35 753

Countries citing papers authored by Mohammad Fard

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Fard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Fard

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Fard. A scholar is included among the top collaborators of Mohammad Fard 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 Mohammad Fard. Mohammad Fard 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.
Fard, Mohammad, et al.. (2025). Structure mode shapes classification using graph convolutional networks in automotive application. Computers & Structures. 314. 107767–107767.
2.
Fard, Mohammad, et al.. (2025). Vibration-induced drowsiness contours: New safety recommendations for the transport industry. Journal of Safety Research. 94. 490–505.
3.
Cheng, Chi‐Tsun, et al.. (2024). Transforming Driver Education: A Comparative Analysis of LLM-Augmented Training and Conventional Instruction for Autonomous Vehicle Technologies. International Journal of Artificial Intelligence in Education. 35(2). 736–773. 9 indexed citations
4.
Fard, Mohammad, et al.. (2024). Cognitive load and task switching in drivers: Implications for road safety in semi-autonomous vehicles. Transportation Research Part F Traffic Psychology and Behaviour. 107. 1175–1197. 6 indexed citations
5.
Cheng, Chi‐Tsun, et al.. (2023). Preparing drivers for the future: Evaluating the effects of training on drivers’ performance in an autonomous vehicle landscape. Transportation Research Part F Traffic Psychology and Behaviour. 98. 280–296. 12 indexed citations
6.
Davy, John L., et al.. (2023). Data augmentation on convolutional neural networks to classify mechanical noise. Applied Acoustics. 203. 109209–109209. 20 indexed citations
7.
Zolfagharian, Ali, et al.. (2023). Additive Manufacturing of Composite Foam Metamaterial Springs for Vibration Isolation. Advanced Engineering Materials. 25(20). 37 indexed citations
8.
Fard, Mohammad, et al.. (2023). Road safety: The influence of vibration frequency on driver drowsiness, reaction time, and driving performance. Applied Ergonomics. 114. 104148–104148. 8 indexed citations
9.
Fard, Mohammad, et al.. (2023). Interrelatedness of steering and lateral position parameters: Recommendations for the assessment of driving performance. Journal of Safety Research. 88. 275–284. 4 indexed citations
10.
Zolfagharian, Ali, et al.. (2022). 3D-Printed Programmable Mechanical Metamaterials for Vibration Isolation and Buckling Control. Sustainability. 14(11). 6831–6831. 66 indexed citations
11.
Fard, Mohammad, et al.. (2021). Mel frequency cepstral coefficient temporal feature integration for classifying squeak and rattle noise. The Journal of the Acoustical Society of America. 150(1). 193–201. 13 indexed citations
12.
Davy, John L., et al.. (2018). The equivalent translational compliance of steel studs with different steel gauge thicknesses. RMIT Research Repository (RMIT University Library). 1 indexed citations
13.
Fard, Mohammad, et al.. (2017). Effects of vibration on occupant driving performance under simulated driving conditions. Applied Ergonomics. 60. 348–355. 20 indexed citations
14.
Fard, Mohammad, et al.. (2016). Acoustic properties of the porous material in a car cabin model. RMIT Research Repository (RMIT University Library). 4 indexed citations
15.
Fard, Mohammad, et al.. (2015). The effects of porous materials on the noise inside a box cavity. RMIT Research Repository (RMIT University Library). 1 indexed citations
16.
Fard, Mohammad & Zhengqing Liu. (2015). Automotive Body Concept Modeling Method for the NVH Performance Optimization. SAE technical papers on CD-ROM/SAE technical paper series. 1. 1 indexed citations
17.
Marzbani, Hormoz, et al.. (2014). Steady-state dynamic steering. RMIT Research Repository (RMIT University Library). 10 indexed citations
18.
Fard, Mohammad, et al.. (2013). Effects of vehicle seat dynamics on ride comfort assessment. RMIT Research Repository (RMIT University Library). 2 indexed citations
19.
Fard, Mohammad, et al.. (2006). Human Postural Dynamics in Response to the Horizontal Vibration. International Journal of Control Automation and Systems. 4(3). 325–332. 3 indexed citations
20.
Fard, Mohammad, Tadashi Ishihara, & Hikaru Inooka. (2004). Identification of the head-neck complex in response to trunk horizontal vibration. Biological Cybernetics. 90(6). 418–426. 21 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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