Marwa Mahmoud

1.6k total citations
33 papers, 870 citations indexed

About

Marwa Mahmoud is a scholar working on Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Applied Psychology. According to data from OpenAlex, Marwa Mahmoud has authored 33 papers receiving a total of 870 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Experimental and Cognitive Psychology, 13 papers in Computer Vision and Pattern Recognition and 7 papers in Applied Psychology. Recurrent topics in Marwa Mahmoud's work include Emotion and Mood Recognition (10 papers), Human Pose and Action Recognition (7 papers) and Digital Mental Health Interventions (7 papers). Marwa Mahmoud is often cited by papers focused on Emotion and Mood Recognition (10 papers), Human Pose and Action Recognition (7 papers) and Digital Mental Health Interventions (7 papers). Marwa Mahmoud collaborates with scholars based in United Kingdom, United States and Netherlands. Marwa Mahmoud's co-authors include Peter Robinson, Tadas Baltrušaitis, Krista M. McLennan, Louis–Philippe Morency, Jonathan Gratch, Stefan Scherer, Giota Stratou, Jill Boberg, Weizhe Lin and Albert Rizzo and has published in prestigious journals such as Bioinformatics, International Journal of Computer Vision and Psychoneuroendocrinology.

In The Last Decade

Marwa Mahmoud

31 papers receiving 823 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marwa Mahmoud United Kingdom 13 426 240 209 163 126 33 870
Catherine Achard France 13 43 0.1× 219 0.9× 193 0.9× 112 0.7× 94 0.7× 34 785
Takatomi Kubo Japan 11 63 0.1× 43 0.2× 77 0.4× 66 0.4× 42 0.3× 45 485
Jonathan Grier United States 10 240 0.6× 70 0.3× 173 0.8× 611 3.7× 98 0.8× 24 1.2k
Andrea Guidi Italy 13 119 0.3× 25 0.1× 64 0.3× 148 0.9× 29 0.2× 20 461
Kazunori Terada Japan 13 84 0.2× 42 0.2× 301 1.4× 189 1.2× 98 0.8× 64 603
Masatoshi Tomita Japan 2 501 1.2× 120 0.5× 362 1.7× 445 2.7× 84 0.7× 3 948
S. Mohammad Mavadati United States 12 799 1.9× 733 3.1× 155 0.7× 260 1.6× 106 0.8× 18 1.2k
Nele Dael Switzerland 12 526 1.2× 150 0.6× 525 2.5× 334 2.0× 52 0.4× 18 958
Albert Russel Netherlands 6 354 0.8× 112 0.5× 156 0.7× 123 0.8× 357 2.8× 16 1.1k
Joseph C. Hager United States 12 747 1.8× 825 3.4× 345 1.7× 532 3.3× 147 1.2× 13 1.6k

Countries citing papers authored by Marwa Mahmoud

Since Specialization
Citations

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

Fields of papers citing papers by Marwa Mahmoud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marwa Mahmoud

This figure shows the co-authorship network connecting the top 25 collaborators of Marwa Mahmoud. A scholar is included among the top collaborators of Marwa Mahmoud 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 Marwa Mahmoud. Marwa Mahmoud 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.
Mahmoud, Marwa, et al.. (2024). Query-Based Topic Modeling and Trend Analysis in Scientific Literature. 1–6. 1 indexed citations
3.
Li, Xinyu & Marwa Mahmoud. (2024). Unlocking the Black Box: Concept-Based Modeling for Interpretable Affective Computing Applications. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1–10. 1 indexed citations
4.
Mahmoud, Marwa, et al.. (2023). Open-Sheep-Face: A Comprehensive Application for Sheep Face Analysis and Pain Estimation. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1–3. 1 indexed citations
5.
Mahmoud, Marwa, et al.. (2023). Towards early prediction of neurodevelopmental disorders: Computational model for Face Touch and Self-adaptors in Infants. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 426–434.
6.
Zamansky, Anna, et al.. (2022). Going Deeper than Tracking: A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions. International Journal of Computer Vision. 131(2). 572–590. 37 indexed citations
7.
Mahmoud, Marwa, et al.. (2021). Multimodal temporal machine learning for Bipolar Disorder and Depression Recognition. Pattern Analysis and Applications. 25(3). 493–504. 37 indexed citations
8.
Lin, Weizhe, et al.. (2020). Multimodal Deep Learning Framework for Mental Disorder Recognition. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 344–350. 45 indexed citations
9.
Lin, Weizhe, et al.. (2020). Automatic Detection of Self-Adaptors for Psychological Distress. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 371–378. 4 indexed citations
10.
McLennan, Krista M. & Marwa Mahmoud. (2019). Development of an Automated Pain Facial Expression Detection System for Sheep (Ovis Aries). Animals. 9(4). 196–196. 53 indexed citations
11.
Pavarini, Gabriela, Rui Sun, Marwa Mahmoud, et al.. (2019). The role of oxytocin in the facial mimicry of affiliative vs. non-affiliative emotions. Psychoneuroendocrinology. 109. 104377–104377. 13 indexed citations
12.
Mahmoud, Marwa, et al.. (2019). Considering Race a Problem of Transfer Learning. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). abs 1412 6980. 100–106. 6 indexed citations
13.
Hewitt, Charlie & Marwa Mahmoud. (2019). Pose-Informed Face Alignment for Extreme Head Pose Variations in Animals. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1–6. 12 indexed citations
14.
Mahmoud, Marwa, et al.. (2018). Analysis of Yawning Behaviour in Spontaneous Expressions of Drowsy Drivers. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 571–576. 21 indexed citations
15.
Mahmoud, Marwa, et al.. (2017). Estimating Sheep Pain Level Using Facial Action Unit Detection. Apollo (University of Cambridge). 394–399. 44 indexed citations
16.
Mahmoud, Marwa, Tadas Baltrušaitis, & Peter Robinson. (2016). Automatic Analysis of Naturalistic Hand-Over-Face Gestures. ACM Transactions on Interactive Intelligent Systems. 6(2). 1–18. 12 indexed citations
17.
Mahmoud, Marwa & Peter Robinson. (2016). Towards automatic analysis of gestures and body expressions in depression. 3 indexed citations
18.
Baltrušaitis, Tadas, Marwa Mahmoud, & Peter Robinson. (2015). Cross-dataset learning and person-specific normalisation for automatic Action Unit detection. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1–6. 263 indexed citations
19.
Mahmoud, Marwa, Tadas Baltrušaitis, & Peter Robinson. (2014). Automatic Detection of Naturalistic Hand-over-Face Gesture Descriptors. Apollo (University of Cambridge). 319–326. 7 indexed citations
20.
Mahmoud, Marwa, Tadas Baltrušaitis, & Peter Robinson. (2012). Crowdsouring in emotion studies across time and culture. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 15–16. 3 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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