Leon Ding
Impact in
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- Quantum and electron transport phenomena
- Quantum Mechanics and Applications
- Quantum many-body systems
- Quantum optics and atomic interactions
- Artificial Intelligence top 10%
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
Papers in
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- Quantum Computing Algorithms and Architecture 3
- Quantum Information and Cryptography 3
- Neural Networks and Reservoir Computing 1
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- Quantum and electron transport phenomena 4
- Co-authors
- Simon Gustavsson (5 shared papers)William D. Oliver (5 shared papers)Bethany M. Niedzielski (5 shared papers)Jonilyn Yoder (4 shared papers)David Kim (4 shared papers)Terry P. Orlando (3 shared papers)Youngkyu Sung (3 shared papers)Alexander Melville (3 shared papers)
- Journals
- Physical Review X (1 paper)Icarus (1 paper)Physical Review Applied (1 paper)PRX Quantum (1 paper)Nature (1 paper)
- Partner nations
- United States
In The Last Decade
Leon Ding
6 papers receiving 191 citations
Peers
Comparison fields: 5 of 17
- Atomic and Molecular Physics, and Optics 140
- Artificial Intelligence 137
- Condensed Matter Physics 14
- Statistical and Nonlinear Physics 9
- Hardware and Architecture 3
Countries citing papers authored by Leon Ding
This map shows the geographic impact of Leon Ding'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 Leon Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leon Ding more than expected).
Fields of papers citing papers by Leon Ding
This network shows the impact of papers produced by Leon Ding. 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 Leon Ding. The network helps show where Leon Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Leon Ding, 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 | 2023 | 77 | |
| 2 | 2020 | 49 | |
| 3 | 2020 | 32 | |
| 4 | 2024 | 18 | |
| 5 | 2024 | 16 | |
| 6 | 2023 | 4 |
About Leon Ding
Leon Ding is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Molecular Biology, Condensed Matter Physics and Astronomy and Astrophysics, having authored 6 papers that have together received 196 indexed citations. Recurring topics across this work include Quantum and electron transport phenomena (4 papers), Quantum Computing Algorithms and Architecture (3 papers), Quantum Information and Cryptography (3 papers), Optical Network Technologies (1 paper), Neural Networks and Reservoir Computing (1 paper), Astro and Planetary Science (1 paper), Physics of Superconductivity and Magnetism (1 paper) and Geomagnetism and Paleomagnetism Studies (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (140 citations), Artificial Intelligence (137 citations), Condensed Matter Physics (14 citations), Statistical and Nonlinear Physics (9 citations) and Hardware and Architecture (3 citations). Leon Ding has collaborated with scholars based in United States. Frequent co-authors include Simon Gustavsson, William D. Oliver, Bethany M. Niedzielski, Jonilyn Yoder, David Kim, Terry P. Orlando, Youngkyu Sung, Alexander Melville, Mollie E. Schwartz and Max Hays. Their work appears in journals such as Physical Review X, Icarus, Physical Review Applied, PRX Quantum and Nature.
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.