Bingbing Nie

765 total citations
68 papers, 499 citations indexed

About

Bingbing Nie is a scholar working on Pulmonary and Respiratory Medicine, Safety, Risk, Reliability and Quality and Automotive Engineering. According to data from OpenAlex, Bingbing Nie has authored 68 papers receiving a total of 499 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Pulmonary and Respiratory Medicine, 29 papers in Safety, Risk, Reliability and Quality and 16 papers in Automotive Engineering. Recurrent topics in Bingbing Nie's work include Automotive and Human Injury Biomechanics (34 papers), Traffic and Road Safety (26 papers) and Autonomous Vehicle Technology and Safety (14 papers). Bingbing Nie is often cited by papers focused on Automotive and Human Injury Biomechanics (34 papers), Traffic and Road Safety (26 papers) and Autonomous Vehicle Technology and Safety (14 papers). Bingbing Nie collaborates with scholars based in China, United States and Japan. Bingbing Nie's co-authors include Qing Zhou, Shengbo Eben Li, Matthew B. Panzer, Richard W. Kent, Jason Forman, Jun Huang, Wentao Chen, Jeff Crandall, Yong Xia and Jeff R. Crandall and has published in prestigious journals such as Scientific Reports, IEEE Access and Journal of Biomechanics.

In The Last Decade

Bingbing Nie

58 papers receiving 488 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bingbing Nie China 14 209 196 89 87 81 68 499
Libo Cao China 15 341 1.6× 248 1.3× 53 0.6× 39 0.4× 83 1.0× 49 707
Robert Thomson Sweden 16 246 1.2× 209 1.1× 49 0.6× 100 1.1× 240 3.0× 74 709
Thomas Seacrist United States 17 354 1.7× 345 1.8× 207 2.3× 101 1.2× 43 0.5× 68 744
Jonas Östh Sweden 13 289 1.4× 125 0.6× 105 1.2× 33 0.4× 41 0.5× 31 460
Niccolò Baldanzini Italy 16 116 0.6× 264 1.3× 115 1.3× 202 2.3× 221 2.7× 73 800
Sheila M. Ebert United States 12 249 1.2× 161 0.8× 168 1.9× 33 0.4× 55 0.7× 52 473
James Lenard United Kingdom 11 200 1.0× 252 1.3× 53 0.6× 81 0.9× 73 0.9× 45 418
Lotta Jakobsson Sweden 16 653 3.1× 448 2.3× 159 1.8× 153 1.8× 144 1.8× 78 934
Jacobo Antona‐Makoshi Japan 13 135 0.6× 133 0.7× 57 0.6× 162 1.9× 19 0.2× 34 388
Jonathan M. Lawrence United States 11 279 1.3× 134 0.7× 17 0.2× 97 1.1× 139 1.7× 25 412

Countries citing papers authored by Bingbing Nie

Since Specialization
Citations

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

Fields of papers citing papers by Bingbing Nie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bingbing Nie

This figure shows the co-authorship network connecting the top 25 collaborators of Bingbing Nie. A scholar is included among the top collaborators of Bingbing Nie 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 Bingbing Nie. Bingbing Nie 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.
Nie, Bingbing, et al.. (2025). Face to planning risk: A hierarchical risk-aware prediction module for the safe planning system. Accident Analysis & Prevention. 213. 107906–107906.
2.
Liu, Zhipeng, et al.. (2025). PODAR: A Collision Risk Model Offering Valid Signals for Vehicular Interactions. IEEE Intelligent Transportation Systems Magazine. 18(1). 6–26.
3.
Li, Quan, Siyuan Liu, Shi Shang, et al.. (2025). Pedestrian decision-making uncertainty in urgent scenarios modulates multi-level, neural hierarchies. Cell Reports Physical Science. 6(2). 102401–102401. 1 indexed citations
4.
Nie, Bingbing, et al.. (2024). Quantifying the Individual Differences of Drivers’ Risk Perception via Potential Damage Risk Model. IEEE Transactions on Intelligent Transportation Systems. 25(7). 8093–8104. 13 indexed citations
5.
Mao, Yingchi, et al.. (2024). Cross‐modal knowledge learning with scene text for fine‐grained image classification. IET Image Processing. 18(6). 1447–1459.
6.
Luo, Yiran, Siyuan Liu, Tsung‐Hsueh Lu, et al.. (2024). Activation strategies and effectiveness of Intelligent safety systems for reducing pedestrian injuries in autonomous vehicles. Accident Analysis & Prevention. 211. 107870–107870.
7.
Meng, Yu, et al.. (2024). Real-Time Reconstruction of Multi-Body Pedestrian Pre-Impact Posture in Collision Accidents From Monocular Images. IEEE Transactions on Intelligent Transportation Systems. 26(1). 457–471.
8.
Zhang, Xiaofei, Jun Li, Xiaorong Gao, et al.. (2024). An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios. Scientific Data. 11(1). 546–546. 3 indexed citations
9.
Zhou, Qing, et al.. (2022). Human injury-based safety decision of automated vehicles. iScience. 25(8). 104703–104703. 11 indexed citations
10.
Li, Quan, et al.. (2021). Kinetic and Kinematic Features of Pedestrian Avoidance Behavior in Motor Vehicle Conflicts. Frontiers in Bioengineering and Biotechnology. 9. 783003–783003. 8 indexed citations
11.
Chen, Wentao, et al.. (2021). A data-driven, kinematic feature-based, near real-time algorithm for injury severity prediction of vehicle occupants. Accident Analysis & Prevention. 156. 106149–106149. 18 indexed citations
12.
Nie, Bingbing, et al.. (2021). Safety envelope of pedestrians upon motor vehicle conflicts identified via active avoidance behaviour. Scientific Reports. 11(1). 3996–3996. 23 indexed citations
13.
Nie, Bingbing, et al.. (2020). Numerical investigation of vehicle occupant injury risks in underbody blast events. Journal of Tsinghua University(Science and Technology). 60(11). 902–909.
14.
Zhou, Qing, et al.. (2019). Are riders of electric two-wheelers safer than bicyclists in collisions with motor vehicles?. Accident Analysis & Prevention. 134. 105336–105336. 37 indexed citations
15.
Forman, Jason, et al.. (2017). Transient and long-time kinetic responses of the cadaveric leg during internal and external foot rotation. Journal of Biomechanics. 53. 196–200. 3 indexed citations
16.
Nie, Bingbing, et al.. (2017). Searching for the “sweet spot”: the foot rotation and parallel engagement of ankle ligaments in maximizing injury tolerance. Biomechanics and Modeling in Mechanobiology. 16(6). 1937–1945. 6 indexed citations
17.
Nie, Bingbing, et al.. (2016). Determination of the in situ mechanical behavior of ankle ligaments. Journal of the mechanical behavior of biomedical materials. 65. 502–512. 16 indexed citations
18.
Subit, Damien, et al.. (2015). The Contribution of Pre-impact Posture on Restrained Occupant Finite Element Model Response in Frontal Impact. Traffic Injury Prevention. 16(sup2). S87–S95. 14 indexed citations
19.
Nie, Bingbing, et al.. (2015). A framework for parametric modeling of ankle ligaments to determine thein situresponse under gross foot motion. Computer Methods in Biomechanics & Biomedical Engineering. 19(12). 1254–1265. 10 indexed citations
20.
Nie, Bingbing, et al.. (2011). A simplified model of pedestrian upper legform impact for estimate of energy-absorption space underneath bonnet lead. 2 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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