Taylor Mordan

744 total citations
11 papers, 216 citations indexed

About

Taylor Mordan is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Artificial Intelligence. According to data from OpenAlex, Taylor Mordan has authored 11 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 4 papers in Automotive Engineering and 4 papers in Artificial Intelligence. Recurrent topics in Taylor Mordan's work include Video Surveillance and Tracking Methods (4 papers), Autonomous Vehicle Technology and Safety (4 papers) and Human Pose and Action Recognition (4 papers). Taylor Mordan is often cited by papers focused on Video Surveillance and Tracking Methods (4 papers), Autonomous Vehicle Technology and Safety (4 papers) and Human Pose and Action Recognition (4 papers). Taylor Mordan collaborates with scholars based in Switzerland, France and Italy. Taylor Mordan's co-authors include Alexandre Alahi, Matthieu Cord, Yuejiang Liu, Parth Kothari, Nicolas Thome, Patrick Pérez, Dongxu Guo, Alberto Del Bimbo, Lorenzo Seidenari and Siyuan Li and has published in prestigious journals such as International Journal of Computer Vision, IEEE Transactions on Intelligent Transportation Systems and Transportation Research Part C Emerging Technologies.

In The Last Decade

Taylor Mordan

10 papers receiving 206 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Taylor Mordan Switzerland	6	142	95	65	33	14	11	216
Haifeng Sang China	9	117 0.8×	48 0.5×	89 1.4×	49 1.5×	10 0.7×	38	209
Irtiza Hasan Italy	6	186 1.3×	69 0.7×	116 1.8×	53 1.6×	24 1.7×	12	256
He Zhao China	8	229 1.6×	86 0.9×	58 0.9×	37 1.1×	11 0.8×	19	290
Onay Urfalıoǧlu Germany	6	128 0.9×	74 0.8×	90 1.4×	17 0.5×	6 0.4×	16	248
Mourad A. Kenk Egypt	6	184 1.3×	48 0.5×	54 0.8×	24 0.7×	4 0.3×	12	256
Apratim Bhattacharyya Germany	6	175 1.2×	84 0.9×	148 2.3×	73 2.2×	21 1.5×	11	262
Kuan-Hui Lee United States	6	291 2.0×	90 0.9×	130 2.0×	63 1.9×	10 0.7×	11	394
Qichang Hu Australia	5	255 1.8×	58 0.6×	41 0.6×	18 0.5×	10 0.7×	6	294
Anselm Haselhoff Germany	9	161 1.1×	61 0.6×	93 1.4×	17 0.5×	21 1.5×	15	256
Caglayan Dicle United States	5	247 1.7×	72 0.8×	44 0.7×	28 0.8×	6 0.4×	6	292

Countries citing papers authored by Taylor Mordan

Since Specialization

Citations

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

Fields of papers citing papers by Taylor Mordan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taylor Mordan

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

Barmpounakis, Emmanouil, et al.. (2025). A New Perspective on Urban Mobility Through Large-Scale Drone Experiments for Smarter, Sustainable Cities. Drones. 9(9). 637–637.

Mordan, Taylor, et al.. (2024). CrossFeat: Semantic Cross-modal Attention for Pedestrian Behavior Forecasting. IEEE Transactions on Intelligent Vehicles. 1–10. 3 indexed citations

Mordan, Taylor, et al.. (2024). Toward Reliable Human Pose Forecasting With Uncertainty. IEEE Robotics and Automation Letters. 9(5). 4447–4454. 1 indexed citations

Mordan, Taylor, et al.. (2023). A generic diffusion-based approach for 3D human pose prediction in the wild. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 8246–8253. 19 indexed citations

Guo, Dongxu, Taylor Mordan, & Alexandre Alahi. (2022). Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion. 2022 International Conference on Robotics and Automation (ICRA). 940–947. 5 indexed citations

Liu, Yuejiang, et al.. (2021). TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive?. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 34. 60 indexed citations

Mordan, Taylor, Matthieu Cord, Patrick Pérez, & Alexandre Alahi. (2021). Detecting 32 Pedestrian Attributes for Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems. 23(8). 11823–11835. 25 indexed citations

Mordan, Taylor, et al.. (2021). Pedestrian intention prediction: A convolutional bottom-up multi-task approach. Transportation Research Part C Emerging Technologies. 130. 103259–103259. 54 indexed citations

Liu, Yuejiang, et al.. (2021). Learning Decoupled Representations for Human Pose Forecasting. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2294–2303. 17 indexed citations

10.

Li, Siyuan, et al.. (2021). A Shared Representation for Photorealistic Driving Simulators. IEEE Transactions on Intelligent Transportation Systems. 23(8). 13835–13845. 3 indexed citations

11.

Mordan, Taylor, et al.. (2018). End-to-End Learning of Latent Deformable Part-Based Representations for Object Detection. International Journal of Computer Vision. 127(11-12). 1659–1679. 29 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.

Explore authors with similar magnitude of impact