Adrian Li
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Speech and dialogue systems
- Natural Language Processing Techniques
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
-
- Reinforcement Learning in Robotics 3
- Topic Modeling 2
- Speech and dialogue systems 2
- Adversarial Robustness in Machine Learning 1
-
- Robot Manipulation and Learning 5
- Co-authors
- Stefanie Tellex (4 shared papers)Daniela Rus (4 shared papers)Ross A. Knepper (4 shared papers)Mrinal Kalakrishnan (3 shared papers)Sergey Levine (2 shared papers)Ali Abdullah Yahya (2 shared papers)Yevgen Chebotar (2 shared papers)Nicholas Roy (2 shared papers)
- Journals
- Autonomous Robots (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)The SAIS review of international affairs (1 paper)arXiv (Cornell University) (1 paper)British Journal of Diabetes (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Adrian Li
8 papers receiving 317 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 208
- Control and Systems Engineering 133
- Computer Vision and Pattern Recognition 117
- Social Psychology 63
- Human-Computer Interaction 8
Countries citing papers authored by Adrian Li
This map shows the geographic impact of Adrian 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 Adrian Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian Li more than expected).
Fields of papers citing papers by Adrian Li
This network shows the impact of papers produced by Adrian 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 Adrian Li. The network helps show where Adrian Li may publish in the future.
Co-authors
The 16 scholars most cited alongside Adrian Li, 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 | 2014 | 107 | |
| 2 | 2017 | 85 | |
| 3 | 2017 | 62 | |
| 4 | 2015 | 58 | |
| 5 | 2019 | 10 | |
| 6 | 2013 | 5 | |
| 7 | 2013 | 5 | |
| 8 | 2022 | 1 | |
| 9 | 2016 | 0 |
About Adrian Li
Adrian Li is a scholar working on Artificial Intelligence, Control and Systems Engineering, General Health Professions, Social Psychology and Sociology and Political Science, having authored 9 papers that have together received 333 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (5 papers), Reinforcement Learning in Robotics (3 papers), Topic Modeling (2 papers), Speech and dialogue systems (2 papers), Chronic Disease Management Strategies (1 paper), Diabetes and associated disorders (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Arctic and Russian Policy Studies (1 paper). The work is most often cited by research in Artificial Intelligence (208 citations), Control and Systems Engineering (133 citations), Computer Vision and Pattern Recognition (117 citations), Social Psychology (63 citations) and Human-Computer Interaction (8 citations). Adrian Li has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Stefanie Tellex, Daniela Rus, Ross A. Knepper, Mrinal Kalakrishnan, Sergey Levine, Ali Abdullah Yahya, Yevgen Chebotar, Nicholas Roy, Nicholas Roy and Stefan Schaal. Their work appears in journals such as Autonomous Robots, DSpace@MIT (Massachusetts Institute of Technology), The SAIS review of international affairs, arXiv (Cornell University) and British Journal of Diabetes.
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.