Mohamed R. Ibrahim

786 total citations
34 papers, 531 citations indexed

About

Mohamed R. Ibrahim is a scholar working on Transportation, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Mohamed R. Ibrahim has authored 34 papers receiving a total of 531 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Transportation, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Mohamed R. Ibrahim's work include Urban Transport and Accessibility (6 papers), Video Surveillance and Tracking Methods (5 papers) and Urban and Rural Development Challenges (5 papers). Mohamed R. Ibrahim is often cited by papers focused on Urban Transport and Accessibility (6 papers), Video Surveillance and Tracking Methods (5 papers) and Urban and Rural Development Challenges (5 papers). Mohamed R. Ibrahim collaborates with scholars based in United Kingdom, Germany and Egypt. Mohamed R. Ibrahim's co-authors include Tao Cheng, James Haworth, Houshmand Masoumi, Nicola Christie, Helena Titheridge, Aldo Lipani, Yang Zhang, Ivar S. Ertesvåg, Geir Skaugen and Mohammad Naeem and has published in prestigious journals such as ACS Nano, PLoS ONE and Scientific Reports.

In The Last Decade

Mohamed R. Ibrahim

29 papers receiving 509 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohamed R. Ibrahim United Kingdom 13 116 94 86 70 67 34 531
Liang Cheng China 12 30 0.3× 61 0.6× 77 0.9× 68 1.0× 56 0.8× 31 602
Ding Ma China 13 143 1.2× 93 1.0× 129 1.5× 78 1.1× 33 0.5× 67 534
Longhao Wang China 11 414 3.6× 79 0.8× 56 0.7× 149 2.1× 112 1.7× 44 791
Biao He China 14 183 1.6× 94 1.0× 26 0.3× 108 1.5× 37 0.6× 38 467
Feilong Wang China 13 230 2.0× 34 0.4× 109 1.3× 62 0.9× 27 0.4× 62 708
Kun Qin China 16 282 2.4× 120 1.3× 191 2.2× 68 1.0× 43 0.6× 50 781
Qiuping Li China 17 536 4.6× 201 2.1× 29 0.3× 151 2.2× 53 0.8× 53 1.0k
Han Yue China 15 152 1.3× 121 1.3× 15 0.2× 60 0.9× 48 0.7× 31 543

Countries citing papers authored by Mohamed R. Ibrahim

Since Specialization
Citations

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

Fields of papers citing papers by Mohamed R. Ibrahim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohamed R. Ibrahim. 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 Mohamed R. Ibrahim. The network helps show where Mohamed R. Ibrahim may publish in the future.

Co-authorship network of co-authors of Mohamed R. Ibrahim

This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed R. Ibrahim. A scholar is included among the top collaborators of Mohamed R. Ibrahim 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 Mohamed R. Ibrahim. Mohamed R. Ibrahim 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.
2.
Ibrahim, Mohamed R. & Terry Lyons. (2025). Transforming CCTV cameras into NO2 sensors at city scale for adaptive policymaking. Scientific Reports. 15(1). 3640–3640.
3.
Ibrahim, Mohamed R.. (2025). TopView: vectorising road users in a bird’s eye view from uncalibrated street-level imagery with deep learning. Neural Computing and Applications. 37(18). 11991–12011.
4.
Ibrahim, Mohamed R.. (2024). Computer vision and statistical insights into cycling near miss dynamics. Scientific Reports. 14(1). 21151–21151. 2 indexed citations
5.
Ibrahim, Mohamed R. & Terry Lyons. (2024). FaceTouch: Detecting hand-to-face touch with supervised contrastive learning to assist in tracing infectious diseases. PLoS ONE. 19(6). e0288670–e0288670. 1 indexed citations
6.
Schillaci, Calogero, et al.. (2022). Borough-level COVID-19 forecasting in London using deep learning techniques and a novel MSE-Moran’s I loss function. Results in Physics. 35. 105374–105374. 11 indexed citations
7.
Ibrahim, Mohamed R., James Haworth, Nicola Christie, & Tao Cheng. (2021). CyclingNet: Detecting cycling near misses from video streams in complex urban scenes with deep learning. UCL Discovery (University College London). 11 indexed citations
8.
Ibrahim, Mohamed R., et al.. (2021). ActivityNET: Neural networks to predict public transport trip purposes from individual smart card data and POIs. Geo-spatial Information Science. 24(4). 711–721. 20 indexed citations
9.
Ibrahim, Mohamed R., et al.. (2021). Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe. PLoS ONE. 16(1). e0246120–e0246120. 26 indexed citations
10.
Ibrahim, Mohamed R., et al.. (2021). Antimicrobial stewardship solutions with a smart innovative tool. Journal of the American Pharmacists Association. 61(5). 581–588.e1. 12 indexed citations
11.
Zhu, Di, et al.. (2020). Semantic enrichment of secondary activities using smart card data and point of interests: a case study in London. Annals of GIS. 27(1). 29–41. 13 indexed citations
12.
Ibrahim, Mohamed R., James Haworth, Nicola Christie, Tao Cheng, & Stephen Hailes. (2020). Cycling near misses: a review of the current methods, challenges and the potential of an AI-embedded system. Transport Reviews. 41(3). 304–328. 11 indexed citations
13.
Ibrahim, Mohamed R., James Haworth, & Tao Cheng. (2019). Weathernet: Recognising weather and visual conditions from street-level images using deep residual learning. UCL Discovery (University College London). 52 indexed citations
14.
Achtstein, Alexander W., Oliver Marquardt, Riccardo Scott, et al.. (2018). Impact of Shell Growth on Recombination Dynamics and Exciton–Phonon Interaction in CdSe–CdS Core–Shell Nanoplatelets. ACS Nano. 12(9). 9476–9483. 35 indexed citations
15.
Ibrahim, Mohamed R. & Houshmand Masoumi. (2018). The nuances of the supplied urban fabric in the MENA Region: Evidence from Alexandria, Egypt. Land Use Policy. 73. 385–399. 9 indexed citations
16.
Ibrahim, Mohamed R.. (2017). A dataset of housing market and self-attitudes towards housing location choices in Alexandria, Egypt. Data in Brief. 11. 543–545. 8 indexed citations
17.
Ibrahim, Mohamed R., Geir Skaugen, & Ivar S. Ertesvåg. (2015). An extended corresponding states equation of state (EoS) for CCS industry. Chemical Engineering Science. 137. 572–582. 4 indexed citations
18.
Ibrahim, Mohamed R. & Ivar S. Ertesvåg. (2014). PVTx Modeling of CO2 Pipeline at Depressurization Conditions Using SPUNG Equation of State (EoS) with a Comparison to SRK. Energy Procedia. 63. 2467–2474. 1 indexed citations
19.
Ibrahim, Mohamed R., Geir Skaugen, Ivar S. Ertesvåg, & Tore Haug–Warberg. (2014). Modeling CO2–water mixture thermodynamics using various equations of state (EoSs) with emphasis on the potential of the SPUNG EoS. Chemical Engineering Science. 113. 22–34. 12 indexed citations
20.
Ibrahim, Mohamed R., et al.. (2012). The Use of Reconfigurable FPGAs in Developing Reliable Satellite On Board Computers. 1 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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