Larry Jackel
Impact in
- Human-Computer Interaction top 10%
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
-
- Robot Manipulation and Learning 3
- Robotics and Automated Systems 2
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- Tactile and Sensory Interactions 4
- Co-authors
- Eric Krotkov (3 shared papers)Christopher T. Orlowski (2 shared papers)Gill A. Pratt (2 shared papers)Xiaoran Fan (4 shared papers)Scott Fish (1 shared paper)Volkan Isler (5 shared papers)Daewon Lee (4 shared papers)Karol Zieba (1 shared paper)
- Journals
- Springer tracts in advanced robotics (2 papers)IEEE Robotics and Automation Letters (1 paper)Journal of Field Robotics (1 paper)Autonomous Robots (1 paper)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United StatesItaly
In The Last Decade
Larry Jackel
11 papers receiving 284 citations
Peers
Comparison fields: 5 of 65
- Human-Computer Interaction 29
- Control and Systems Engineering 104
- Computer Vision and Pattern Recognition 85
- Automotive Engineering 46
- Biomedical Engineering 102
Countries citing papers authored by Larry Jackel
This map shows the geographic impact of Larry Jackel'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 Larry Jackel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Larry Jackel more than expected).
Fields of papers citing papers by Larry Jackel
This network shows the impact of papers produced by Larry Jackel. 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 Larry Jackel. The network helps show where Larry Jackel may publish in the future.
Co-authors
The 25 scholars most cited alongside Larry Jackel, 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 | 2016 | 111 | |
| 2 | VisualBackProp: visualizing CNNs for autonomous driving. | 2016 | 41 |
| 3 | 2006 | 40 | |
| 4 | 2018 | 36 | |
| 5 | 2022 | 21 | |
| 6 | 2020 | 16 | |
| 7 | 2021 | 12 | |
| 8 | 2008 | 12 | |
| 9 | 2023 | 5 | |
| 10 | 2022 | 4 | |
| 11 | 2023 | 2 |
About Larry Jackel
Larry Jackel is a scholar working on Control and Systems Engineering, Cognitive Neuroscience, Human-Computer Interaction, Biomedical Engineering and Artificial Intelligence, having authored 11 papers that have together received 300 indexed citations. Recurring topics across this work include Tactile and Sensory Interactions (4 papers), Robot Manipulation and Learning (3 papers), Advanced Sensor and Energy Harvesting Materials (3 papers), Anomaly Detection Techniques and Applications (2 papers), Robotics and Automated Systems (2 papers), Hand Gesture Recognition Systems (1 paper), Interactive and Immersive Displays (1 paper) and Disaster Response and Management (1 paper). The work is most often cited by research in Human-Computer Interaction (29 citations), Control and Systems Engineering (104 citations), Computer Vision and Pattern Recognition (85 citations), Automotive Engineering (46 citations) and Biomedical Engineering (102 citations). Larry Jackel has collaborated with scholars based in United States and Italy. Frequent co-authors include Eric Krotkov, Christopher T. Orlowski, Gill A. Pratt, Xiaoran Fan, Scott Fish, Volkan Isler, Daewon Lee, Karol Zieba, Richard Howard and Krzysztof Choromański. Their work appears in journals such as Springer tracts in advanced robotics, IEEE Robotics and Automation Letters, Journal of Field Robotics, Autonomous Robots 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.