Daniel Liu
Impact in
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- Advanced Optical Sensing Technologies
Papers in
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- Adversarial Robustness in Machine Learning 3
- Algorithms and Data Compression 3
- Machine Learning and Algorithms 2
- Co-authors
- Ronald Yu (3 shared papers)Hao Su (2 shared papers)Michael P. Fitz (1 shared paper)Martin Steinegger (1 shared paper)Ana J. Coito (1 shared paper)Hiroyuki Kato (1 shared paper)Ronald W. Busuttil (1 shared paper)Sergio Duarte (1 shared paper)
- Journals
- PeerJ (2 papers)Bioinformatics (1 paper)Algorithms for Molecular Biology (1 paper)Proceedings of the VLDB Endowment (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesTaiwanSwitzerland
In The Last Decade
Daniel Liu
22 papers receiving 269 citations
Peers
Comparison fields: 5 of 70
- Instrumentation 23
- Computer Graphics and Computer-Aided Design 15
- Artificial Intelligence 136
- Health Informatics 4
- Computer Vision and Pattern Recognition 55
Countries citing papers authored by Daniel Liu
This map shows the geographic impact of Daniel Liu'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 Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Liu more than expected).
Fields of papers citing papers by Daniel Liu
This network shows the impact of papers produced by Daniel Liu. 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 Liu. The network helps show where Daniel Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Liu, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 122 | |
| 2 | 2020 | 30 | |
| 3 | 2015 | 27 | |
| 4 | 2019 | 17 | |
| 5 | 2006 | 14 | |
| 6 | 2023 | 11 | |
| 7 | 2006 | 9 | |
| 8 | Adversarial point perturbations on 3D objects | 2019 | 6 |
| 9 | 2024 | 6 | |
| 10 | 2009 | 5 | |
| 11 | 2019 | 4 | |
| 12 | 2011 | 4 | |
| 13 | 2022 | 4 | |
| 14 | 2019 | 3 | |
| 15 | 2018 | 3 | |
| 16 | Simulation model of Pacinian corpuscle for haptic system design | 2011 | 3 |
| 17 | 2020 | 2 | |
| 18 | 2019 | 1 | |
| 19 | System Demonstration of MRAM Co-designed Processing-in-Memory CNN Accelerator for Mobile and IoT Applications. | 2019 | 1 |
| 20 | 2025 | 1 |
About Daniel Liu
Daniel Liu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Molecular Biology and Management Science and Operations Research, having authored 24 papers that have together received 275 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Algorithms and Data Compression (3 papers), Advanced Database Systems and Queries (2 papers), Data Quality and Management (2 papers), Machine Learning and Algorithms (2 papers), High-Velocity Impact and Material Behavior (2 papers), VLSI and Analog Circuit Testing (2 papers) and Genomics and Phylogenetic Studies (2 papers). The work is most often cited by research in Instrumentation (23 citations), Computer Graphics and Computer-Aided Design (15 citations), Artificial Intelligence (136 citations), Health Informatics (4 citations) and Computer Vision and Pattern Recognition (55 citations). Daniel Liu has collaborated with scholars based in United States, Taiwan and Switzerland. Frequent co-authors include Ronald Yu, Hao Su, Michael P. Fitz, Martin Steinegger, Ana J. Coito, Hiroyuki Kato, Ronald W. Busuttil, Sergio Duarte, Hao Su and Shanchieh Jay Yang. Their work appears in journals such as PeerJ, Bioinformatics, Algorithms for Molecular Biology, Proceedings of the VLDB Endowment and PLoS ONE.
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.