Yunzhu Li
- Biomedical Engineering top 2%
- Cognitive Neuroscience top 2%
- Mechanical Engineering top 5%
- Electrical and Electronic Engineering top 10%
- Human-Computer Interaction top 1%
- Co-authors
- Antonio TorralbaWojciech MatusikJun-Yan ZhuPetr KellnhoferSubramanian SundaramGang PeiJing LiJie Ji
- Topics
- Robot Manipulation and Learning (8 papers)Tactile and Sensory Interactions (6 papers)Advanced Thermodynamic Systems and Engines (5 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Yunzhu Li
28 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Biomedical Engineering 1.1k
- Cognitive Neuroscience 755
- Mechanical Engineering 480
- Electrical and Electronic Engineering 323
- Human-Computer Interaction 285
Countries citing papers authored by Yunzhu Li
This map shows the geographic impact of Yunzhu Li'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 Yunzhu Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yunzhu Li more than expected).
Fields of papers citing papers by Yunzhu Li
This network shows the impact of papers produced by Yunzhu Li. 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 Yunzhu Li. The network helps show where Yunzhu Li may publish in the future.
Co-authorship network of co-authors of Yunzhu Li
This figure shows the co-authorship network connecting the top 25 collaborators of Yunzhu Li. A scholar is included among the top collaborators of Yunzhu Li 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 Yunzhu Li. Yunzhu Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | Adaptive tactile interaction transfer via digitally embroidered smart glovesbreakdown → | 60 |
| 6 | 4 | |
| 7 | 6 | |
| 8 | 16 | |
| 9 | 5 | |
| 10 | 11 | |
| 11 | 18 | |
| 12 | 4 | |
| 13 | 8 | |
| 14 | 45 | |
| 15 | Causal Discovery in Physical Systems from Videos | 2 |
| 16 | Visual Grounding of Learned Physical Models | 3 |
| 17 | Learning the signatures of the human grasp using a scalable tactile glovebreakdown → | 880 |
| 18 | 25 | |
| 19 | 28 | |
| 20 | 23 |
About Yunzhu Li
Yunzhu Li is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Human-Computer Interaction, having authored 33 papers that have together received 1.8k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (8 papers), Tactile and Sensory Interactions (6 papers) and Advanced Thermodynamic Systems and Engines (5 papers). The work is most often cited by research in Human-Computer Interaction (285 citations), Cognitive Neuroscience (755 citations) and Biomedical Engineering (1.1k citations). Yunzhu Li has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Antonio Torralba, Wojciech Matusik, Jun-Yan Zhu, Petr Kellnhofer, Subramanian Sundaram, Gang Pei, Jing Li, Jie Ji, Dongyue Wang and Michael Foshey. Their work appears in journals such as Nature, Nature Communications and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.