Steven W. Chen
Impact in
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses
- Environmental Engineering top 10%
- Remote Sensing and LiDAR Applications
Papers in
- Geology 1
- Co-authors
- Vijay KumarChao QuCamillo J. TaylorJnaneshwar DasShreyas S. ShivakumarFernando CladeraXu LiuBrian A. Bartz
- Journals
- IEEE Robotics and Automation Letters (2 papers)IEEE Micro (1 paper)The Journal of Organic Chemistry (1 paper)Arthroscopy Techniques (2 papers)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United StatesBrazil
In The Last Decade
Steven W. Chen
10 papers receiving 660 citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Analytical Chemistry 134
- Environmental Engineering 142
- Plant Science 350
- Geology 49
- Computer Vision and Pattern Recognition 160
Countries citing papers authored by Steven W. Chen
This map shows the geographic impact of Steven W. Chen'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 Steven W. Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven W. Chen more than expected).
Fields of papers citing papers by Steven W. Chen
This network shows the impact of papers produced by Steven W. Chen. 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 Steven W. Chen. The network helps show where Steven W. Chen may publish in the future.
Co-authors
The 15 scholars most cited alongside Steven W. Chen, 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 | 2022 | 30 | |
| 2 | 2022 | 64 | |
| 3 | 2021 | 3 | |
| 4 | 2020 | 118 | |
| 5 | 2019 | 26 | |
| 6 | 2019 | 12 | |
| 7 | 2018 | 89 | |
| 8 | 2018 | 14 | |
| 9 | 2018 | 15 | |
| 10 | Counting Apples and Oranges With Deep Learning: A Data-Driven Approach Hit paper breakdown → | 2017 | 322 |
About Steven W. Chen
Steven W. Chen is a scholar working on Geology, Biophysics, Computer Vision and Pattern Recognition, Environmental Engineering and Aerospace Engineering, having authored 10 papers that have together received 693 indexed citations. Recurring topics across this work include Smart Agriculture and AI (3 papers), Robotics and Sensor-Based Localization (3 papers), Shoulder and Clavicle Injuries (2 papers), Remote Sensing in Agriculture (2 papers), Remote Sensing and LiDAR Applications (2 papers), Robotic Path Planning Algorithms (2 papers), Shoulder Injury and Treatment (2 papers) and Catalytic C–H Functionalization Methods (1 paper). The work is most often cited by research in Analytical Chemistry (134 citations), Environmental Engineering (142 citations), Plant Science (350 citations), Geology (49 citations) and Computer Vision and Pattern Recognition (160 citations). Steven W. Chen has collaborated with scholars based in United States and Brazil. Frequent co-authors include Vijay Kumar, Chao Qu, Camillo J. Taylor, Jnaneshwar Das, Shreyas S. Shivakumar, Fernando Cladera, Xu Liu, Xu Liu, Brian A. Bartz and William T. Pennington. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Micro, The Journal of Organic Chemistry, Arthroscopy Techniques and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.