Iris Cong
Impact in
- Artificial Intelligence top 1%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
Papers in ⓘ
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- Topological Materials and Phenomena 3
- Quantum and electron transport phenomena 3
- Quantum many-body systems 3
- Quantum Mechanics and Applications 3
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- Quantum Information and Cryptography 7
- Quantum Computing Algorithms and Architecture 6
- Machine Learning and Algorithms 1
- Co-authors
- Mikhail D. Lukin (6 shared papers)Soonwon Choi (2 shared papers)Luming Duan (1 shared paper)Zhenghan Wang (3 shared papers)Meng Cheng (3 shared papers)Alexander Keesling (1 shared paper)Harry Levine (1 shared paper)Sheng-Tao Wang (1 shared paper)
- Journals
- Physical Review X (3 papers)Nature Communications (1 paper)New Journal of Physics (1 paper)Physical Review Letters (1 paper)Communications in Mathematical Physics (1 paper)
- Partner nations
- United StatesCanadaAustria
In The Last Decade
Iris Cong
10 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 931
- Computational Mathematics 8
- Atomic and Molecular Physics, and Optics 412
- Computational Theory and Mathematics 193
- Biophysics 22
Countries citing papers authored by Iris Cong
This map shows the geographic impact of Iris Cong'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 Iris Cong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iris Cong more than expected).
Fields of papers citing papers by Iris Cong
This network shows the impact of papers produced by Iris Cong. 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 Iris Cong. The network helps show where Iris Cong may publish in the future.
Co-authors
The 25 scholars most cited alongside Iris Cong, 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 | Quantum convolutional neural networks Hit paper breakdown → | 2019 | 810 |
| 2 | 2022 | 105 | |
| 3 | 2016 | 90 | |
| 4 | 2022 | 34 | |
| 5 | 2017 | 32 | |
| 6 | 2017 | 27 | |
| 7 | 2017 | 19 | |
| 8 | 2024 | 18 | |
| 9 | 2024 | 8 | |
| 10 | 2021 | 5 |
About Iris Cong
Iris Cong is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Geometry and Topology, Biomedical Engineering and Infectious Diseases, having authored 10 papers that have together received 1.1k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (7 papers), Quantum Computing Algorithms and Architecture (6 papers), Topological Materials and Phenomena (3 papers), Quantum and electron transport phenomena (3 papers), Quantum many-body systems (3 papers), Quantum Mechanics and Applications (3 papers), Machine Learning and Algorithms (1 paper) and Molecular Communication and Nanonetworks (1 paper). The work is most often cited by research in Artificial Intelligence (931 citations), Computational Mathematics (8 citations), Atomic and Molecular Physics, and Optics (412 citations), Computational Theory and Mathematics (193 citations) and Biophysics (22 citations). Iris Cong has collaborated with scholars based in United States, Canada and Austria. Frequent co-authors include Mikhail D. Lukin, Soonwon Choi, Luming Duan, Zhenghan Wang, Meng Cheng, Alexander Keesling, Harry Levine, Sheng-Tao Wang, Dolev Bluvstein and Beni Yoshida. Their work appears in journals such as Physical Review X, Nature Communications, New Journal of Physics, Physical Review Letters and Communications in Mathematical Physics.
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.