Daniel Bochen Tan
Impact in
- Artificial Intelligence top 10%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
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- Parallel Computing and Optimization Techniques
Papers in
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- Quantum Computing Algorithms and Architecture 12
- Quantum Information and Cryptography 11
- Neural Networks and Reservoir Computing 1
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- Quantum Mechanics and Applications 2
- Co-authors
- Jason Cong (11 shared papers)Dolev Bluvstein (2 shared papers)Mikhail D. Lukin (3 shared papers)Wan-Hsuan Lin (5 shared papers)Nikolaj Bjørner (1 shared paper)Murphy Yuezhen Niu (1 shared paper)Song Han (2 shared papers)Jiaqi Gu (2 shared papers)
- Journals
- IEEE Transactions on Computers (1 paper)IEEE Journal on Emerging and Selected Topics in Circuits and Systems (1 paper)Quantum (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)
- Partner nations
- United States
In The Last Decade
Daniel Bochen Tan
11 papers receiving 173 citations
Peers
Comparison fields: 5 of 14
- Artificial Intelligence 169
- Hardware and Architecture 28
- Computational Theory and Mathematics 46
- Atomic and Molecular Physics, and Optics 53
- Software 4
Countries citing papers authored by Daniel Bochen Tan
This map shows the geographic impact of Daniel Bochen Tan'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 Daniel Bochen Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Bochen Tan more than expected).
Fields of papers citing papers by Daniel Bochen Tan
This network shows the impact of papers produced by Daniel Bochen Tan. 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 Daniel Bochen Tan. The network helps show where Daniel Bochen Tan may publish in the future.
Co-authors
The 16 scholars most cited alongside Daniel Bochen Tan, 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 | 2020 | 59 | |
| 2 | 2021 | 23 | |
| 3 | 2023 | 20 | |
| 4 | 2024 | 19 | |
| 5 | 2022 | 16 | |
| 6 | 2022 | 13 | |
| 7 | 2024 | 12 | |
| 8 | 2024 | 9 | |
| 9 | 2025 | 5 | |
| 10 | 2025 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 0 |
About Daniel Bochen Tan
Daniel Bochen Tan is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Electrical and Electronic Engineering and Hardware and Architecture, having authored 12 papers that have together received 179 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (12 papers), Quantum Information and Cryptography (11 papers), Quantum-Dot Cellular Automata (3 papers), Low-power high-performance VLSI design (2 papers), Parallel Computing and Optimization Techniques (2 papers), Quantum Mechanics and Applications (2 papers), Cloud Computing and Resource Management (1 paper) and Neural Networks and Reservoir Computing (1 paper). The work is most often cited by research in Artificial Intelligence (169 citations), Hardware and Architecture (28 citations), Computational Theory and Mathematics (46 citations), Atomic and Molecular Physics, and Optics (53 citations) and Software (4 citations). Daniel Bochen Tan has collaborated with scholars based in United States. Frequent co-authors include Jason Cong, Dolev Bluvstein, Mikhail D. Lukin, Wan-Hsuan Lin, Nikolaj Bjørner, Murphy Yuezhen Niu, Song Han, Jiaqi Gu, David Z. Pan and Umut A. Acar. Their work appears in journals such as IEEE Transactions on Computers, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Quantum and DSpace@MIT (Massachusetts Institute of Technology).
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.