Liangda Li
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
Papers in
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- Bayesian Methods and Mixture Models 4
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- Diffusion and Search Dynamics 4
- Co-authors
- Hongyuan Zha (11 shared papers)Yi Chang (7 shared papers)Hongbo Deng (6 shared papers)Yong Yu (2 shared papers)Ke Zhou (2 shared papers)Gui-Rong Xue (2 shared papers)Anlei Dong (4 shared papers)Ricardo Baeza‐Yates (2 shared papers)
- Journals
- Gastroenterology (1 paper)Plant Diversity (1 paper)Frontiers in Immunology (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)The American Journal of Gastroenterology (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Liangda Li
22 papers receiving 391 citations
Peers
Comparison fields: 5 of 72
- Computational Mathematics 4
- Artificial Intelligence 213
- Information Systems 140
- Signal Processing 57
- Computer Vision and Pattern Recognition 94
Countries citing papers authored by Liangda Li
This map shows the geographic impact of Liangda 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 Liangda Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangda Li more than expected).
Fields of papers citing papers by Liangda Li
This network shows the impact of papers produced by Liangda 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 Liangda Li. The network helps show where Liangda Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Liangda 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
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 98 | |
| 2 | 2014 | 46 | |
| 3 | 2015 | 37 | |
| 4 | 2011 | 32 | |
| 5 | 2017 | 31 | |
| 6 | 2012 | 25 | |
| 7 | 2019 | 23 | |
| 8 | 2014 | 22 | |
| 9 | 2017 | 21 | |
| 10 | 2013 | 19 | |
| 11 | 2019 | 14 | |
| 12 | 2019 | 11 | |
| 13 | 2020 | 10 | |
| 14 | 2015 | 8 | |
| 15 | 2016 | 8 | |
| 16 | 2017 | 7 | |
| 17 | Household structure analysis via hawkes processes for enhancing energy disaggregation | 2016 | 6 |
| 18 | 2015 | 4 | |
| 19 | 2018 | 3 | |
| 20 | 2022 | 1 |
About Liangda Li
Liangda Li is a scholar working on Artificial Intelligence, Molecular Biology, Applied Mathematics, Information Systems and Signal Processing, having authored 22 papers that have together received 428 indexed citations. Recurring topics across this work include Point processes and geometric inequalities (6 papers), Information Retrieval and Search Behavior (4 papers), Diffusion and Search Dynamics (4 papers), Bayesian Methods and Mixture Models (4 papers), Web Data Mining and Analysis (3 papers), Economic and Environmental Valuation (2 papers), Noise Effects and Management (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Computational Mathematics (4 citations), Artificial Intelligence (213 citations), Information Systems (140 citations), Signal Processing (57 citations) and Computer Vision and Pattern Recognition (94 citations). Liangda Li has collaborated with scholars based in United States and China. Frequent co-authors include Hongyuan Zha, Yi Chang, Hongbo Deng, Yong Yu, Ke Zhou, Gui-Rong Xue, Anlei Dong, Ricardo Baeza‐Yates, Guy Lebanon and Haesun Park. Their work appears in journals such as Gastroenterology, Plant Diversity, Frontiers in Immunology, ACM Transactions on Intelligent Systems and Technology and The American Journal of Gastroenterology.
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.