Mohammed Elhenawy

1.8k total citations
111 papers, 974 citations indexed

About

Mohammed Elhenawy is a scholar working on Building and Construction, Transportation and Automotive Engineering. According to data from OpenAlex, Mohammed Elhenawy has authored 111 papers receiving a total of 974 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Building and Construction, 40 papers in Transportation and 34 papers in Automotive Engineering. Recurrent topics in Mohammed Elhenawy's work include Traffic Prediction and Management Techniques (37 papers), Transportation Planning and Optimization (26 papers) and Urban Transport and Accessibility (22 papers). Mohammed Elhenawy is often cited by papers focused on Traffic Prediction and Management Techniques (37 papers), Transportation Planning and Optimization (26 papers) and Urban Transport and Accessibility (22 papers). Mohammed Elhenawy collaborates with scholars based in Australia, United States and Palestinian Territory. Mohammed Elhenawy's co-authors include Hesham Rakha, Huthaifa I. Ashqar, Andry Rakotonirainy, Mohammed Almannaa, Mahmoud Masoud, Sébastien Glaser, Ahmed Elbery, Hao Chen, Ihab El-Shawarby and Arash Jahangiri and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Mohammed Elhenawy

98 papers receiving 929 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammed Elhenawy Australia 16 381 368 360 256 193 111 974
Emmanouil Barmpounakis Switzerland 16 238 0.6× 469 1.3× 252 0.7× 281 1.1× 248 1.3× 34 1.0k
Muhammad Adnan Belgium 17 358 0.9× 294 0.8× 214 0.6× 176 0.7× 174 0.9× 81 976
Rosaldo J. F. Rossetti Portugal 18 374 1.0× 362 1.0× 260 0.7× 318 1.2× 68 0.4× 113 988
Xianbiao Hu United States 18 502 1.3× 431 1.2× 343 1.0× 307 1.2× 161 0.8× 77 1.0k
Jingqiu Guo China 17 308 0.8× 297 0.8× 328 0.9× 386 1.5× 199 1.0× 45 773
Ye Tian China 17 307 0.8× 442 1.2× 207 0.6× 267 1.0× 122 0.6× 88 789
Arash Jahangiri United States 13 289 0.8× 166 0.5× 251 0.7× 111 0.4× 255 1.3× 39 688
Keshuang Tang China 20 378 1.0× 278 0.8× 544 1.5× 560 2.2× 289 1.5× 87 959
Xu Qu China 18 437 1.1× 589 1.6× 578 1.6× 852 3.3× 324 1.7× 71 1.3k
Chaozhong Wu China 14 237 0.6× 227 0.6× 151 0.4× 155 0.6× 403 2.1× 39 1.0k

Countries citing papers authored by Mohammed Elhenawy

Since Specialization
Citations

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

Fields of papers citing papers by Mohammed Elhenawy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammed Elhenawy

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Elhenawy. A scholar is included among the top collaborators of Mohammed Elhenawy 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 Mohammed Elhenawy. Mohammed Elhenawy 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.
Alhadidi, Taqwa I., et al.. (2025). Investigating patterns of freeway crashes in Jordan: Findings from a text mining approach. Results in Engineering. 26. 104413–104413. 5 indexed citations
2.
Alhadidi, Taqwa I., et al.. (2025). AI for Data Quality Auditing: Detecting Mislabeled Work Zone Crashes Using Large Language Models. Algorithms. 18(6). 317–317.
3.
4.
Elhenawy, Mohammed, et al.. (2025). A Cross-Cultural Crash Pattern Analysis in the United States and Jordan Using BERT and SHAP. Electronics. 14(2). 272–272. 2 indexed citations
5.
Elhenawy, Mohammed, et al.. (2025). Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding. Electronics. 14(7). 1282–1282. 4 indexed citations
6.
Almannaa, Mohammed, et al.. (2024). Temporal Shifts in E-Scooter Rider Perspectives: A Longitudinal Investigation in Riyadh, Saudi Arabia. Sustainability. 16(9). 3759–3759. 1 indexed citations
7.
Alhadidi, Taqwa I., et al.. (2024). Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics. 1–6. 8 indexed citations
8.
Ashqar, Huthaifa I., et al.. (2024). Incorporating driving behavior into vehicle fuel consumption prediction: methodology development and testing. SHILAP Revista de lepidopterología. 5(1). 4 indexed citations
9.
Elhenawy, Mohammed, et al.. (2024). Advancing Roadway Sign Detection with YOLO Models and Transfer Learning. 1–4. 2 indexed citations
10.
Elhenawy, Mohammed, et al.. (2024). Automated Pavement Cracks Detection and Classification Using Deep Learning. 1–5. 5 indexed citations
11.
Ashqar, Huthaifa I., et al.. (2024). Leveraging Multimodal Large Language Models (MLLMs) for Enhanced Object Detection and Scene Understanding in Thermal Images for Autonomous Driving Systems. SHILAP Revista de lepidopterología. 5(4). 508–526. 13 indexed citations
12.
Ashqar, Huthaifa I., et al.. (2024). Using Multimodal Large Language Models (MLLMs) for Automated Detection of Traffic Safety-Critical Events. SHILAP Revista de lepidopterología. 6(3). 1571–1590. 21 indexed citations
13.
Elhenawy, Mohammed, et al.. (2023). Deep RNN Based Prediction of Driver’s Intended Movements at Intersection Using Cooperative Awareness Messages. IEEE Transactions on Intelligent Transportation Systems. 24(7). 6902–6921. 18 indexed citations
14.
Masoud, Mahmoud, Mohammed Elhenawy, Shi Qiang Liu, et al.. (2023). A Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers. Sustainability. 15(3). 1869–1869. 2 indexed citations
15.
Ashqar, Huthaifa I., et al.. (2022). Application of Unsupervised Machine Learning Classification for the Analysis of Driver Behavior in Work Zones in the State of Qatar. Sustainability. 14(22). 15184–15184. 13 indexed citations
16.
Elhenawy, Mohammed, et al.. (2020). A framework for testing independence between lane change and cooperative intelligent transportation system. PLoS ONE. 15(2). e0229289–e0229289. 3 indexed citations
17.
Elhenawy, Mohammed, Youssef Bichiou, & Hesham Rakha. (2019). A heuristic algorithm for rebalancing large-scale bike sharing systems using multiple trucks. QUT ePrints (Queensland University of Technology). 2 indexed citations
18.
Elhenawy, Mohammed & Hesham Rakha. (2016). Traffic Stream Speed Short-term Prediction using Machine Learning Techniques: I-66 Case Study. Transportation Research Board 95th Annual MeetingTransportation Research Board. 2 indexed citations
19.
Elhenawy, Mohammed & Hesham Rakha. (2016). Expected Travel Time and Reliability Prediction Using Mixture Linear Regression. Transportation Research Board 95th Annual MeetingTransportation Research Board. 1 indexed citations
20.
Elhenawy, Mohammed, et al.. (2015). Traffic Congestion Identification Considering Weather and Visibility Conditions Using Mixture Linear Regression. Transportation Research Board 94th Annual MeetingTransportation Research Board. 7 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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