Christopher Tay
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
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- Robotic Path Planning Algorithms
- Video Surveillance and Tracking Methods
Papers in
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- Target Tracking and Data Fusion in Sensor Networks 4
- Anomaly Detection Techniques and Applications 2
- Reinforcement Learning in Robotics 1
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- Video Surveillance and Tracking Methods 3
- Robotic Path Planning Algorithms 2
- Co-authors
- Christian Laugier (7 shared papers)Kamel Mekhnacha (4 shared papers)Chiara Fulgenzi (2 shared papers)Anne Spalanzani (2 shared papers)Amaury Nègre (2 shared papers)John-David Yoder (1 shared paper)I.E. Paromtchik (2 shared papers)Mathias Perrollaz (2 shared papers)
- Journals
- IEEE Intelligent Transportation Systems Magazine (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (3 papers)
- Partner nations
- FranceUnited States
In The Last Decade
Christopher Tay
7 papers receiving 370 citations
Peers
Comparison fields: 5 of 44
- Automotive Engineering 243
- Computer Vision and Pattern Recognition 188
- Safety, Risk, Reliability and Quality 78
- Building and Construction 67
- Control and Systems Engineering 101
Countries citing papers authored by Christopher Tay
This map shows the geographic impact of Christopher Tay'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 Christopher Tay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Tay more than expected).
Fields of papers citing papers by Christopher Tay
This network shows the impact of papers produced by Christopher Tay. 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 Christopher Tay. The network helps show where Christopher Tay may publish in the future.
Co-authors
The 11 scholars most cited alongside Christopher Tay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 214 | |
| 2 | 2008 | 90 | |
| 3 | 2006 | 46 | |
| 4 | Risk based motion planning and navigation in uncertain dynamic environment | 2010 | 33 |
| 5 | 2010 | 2 | |
| 6 | Velocity Estimation on the Bayesian Occupancy Filter for Multi-Target Tracking | 2006 | 2 |
| 7 | An Efficient Formulation of the Bayesian Occupation Filter for Target Tracking in Dynamic Environments | 2006 | 1 |
About Christopher Tay
Christopher Tay is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Automotive Engineering, Aerospace Engineering and Ocean Engineering, having authored 7 papers that have together received 388 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (4 papers), Video Surveillance and Tracking Methods (3 papers), Robotics and Sensor-Based Localization (2 papers), Robotic Path Planning Algorithms (2 papers), Autonomous Vehicle Technology and Safety (2 papers), Anomaly Detection Techniques and Applications (2 papers), Evacuation and Crowd Dynamics (1 paper) and Reinforcement Learning in Robotics (1 paper). The work is most often cited by research in Automotive Engineering (243 citations), Computer Vision and Pattern Recognition (188 citations), Safety, Risk, Reliability and Quality (78 citations), Building and Construction (67 citations) and Control and Systems Engineering (101 citations). Christopher Tay has collaborated with scholars based in France and United States. Frequent co-authors include Christian Laugier, Kamel Mekhnacha, Chiara Fulgenzi, Anne Spalanzani, Amaury Nègre, John-David Yoder, I.E. Paromtchik, Mathias Perrollaz, Yong Mao and Manuel Yguel. Their work appears in journals such as IEEE Intelligent Transportation Systems Magazine and HAL (Le Centre pour la Communication Scientifique Directe).
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.