Marion Lepert
Impact in
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- Advanced Photocatalysis Techniques
- TiO2 Photocatalysis and Solar Cells
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- Multimodal Machine Learning Applications
Papers in
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- Robot Manipulation and Learning 3
- Robotic Mechanisms and Dynamics 1
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- Multimodal Machine Learning Applications 2
- Co-authors
- Jeannette Bohg (4 shared papers)Rika Antonova (3 shared papers)Jimmy Wu (2 shared papers)Szymon Rusinkiewicz (2 shared papers)Andy Zeng (2 shared papers)Thomas Funkhouser (2 shared papers)Shuran Song (2 shared papers)Hanyu Wang (1 shared paper)
- Journals
- Autonomous Robots (1 paper)Nanoscale (1 paper)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Marion Lepert
5 papers receiving 289 citations
Marion Lepert's Hit Papers
Peers
Comparison fields: 5 of 40
- Renewable Energy, Sustainability and the Environment 88
- Computer Vision and Pattern Recognition 72
- Control and Systems Engineering 70
- Artificial Intelligence 88
- Human-Computer Interaction 12
Countries citing papers authored by Marion Lepert
This map shows the geographic impact of Marion Lepert'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 Marion Lepert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marion Lepert more than expected).
Fields of papers citing papers by Marion Lepert
This network shows the impact of papers produced by Marion Lepert. 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 Marion Lepert. The network helps show where Marion Lepert may publish in the future.
Co-authors
The 14 scholars most cited alongside Marion Lepert, 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 | TidyBot: personalized robot assistance with large language models Hit paper breakdown → | 2023 | 109 |
| 2 | 2012 | 101 | |
| 3 | 2023 | 50 | |
| 4 | 2021 | 24 | |
| 5 | 2023 | 9 |
About Marion Lepert
Marion Lepert is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Computer Science Applications, having authored 5 papers that have together received 293 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (3 papers), Multimodal Machine Learning Applications (2 papers), Tactile and Sensory Interactions (1 paper), TiO2 Photocatalysis and Solar Cells (1 paper), Natural Language Processing Techniques (1 paper), Copper-based nanomaterials and applications (1 paper), Advanced Photocatalysis Techniques (1 paper) and Robotic Mechanisms and Dynamics (1 paper). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (88 citations), Computer Vision and Pattern Recognition (72 citations), Control and Systems Engineering (70 citations), Artificial Intelligence (88 citations) and Human-Computer Interaction (12 citations). Marion Lepert has collaborated with scholars based in United States and China. Frequent co-authors include Jeannette Bohg, Rika Antonova, Jimmy Wu, Szymon Rusinkiewicz, Andy Zeng, Thomas Funkhouser, Shuran Song, Hanyu Wang, Gongming Wang and Yat Li. Their work appears in journals such as Autonomous Robots, Nanoscale 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.