Daniel Ruderman
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- Advanced Vision and Imaging 4
- Cognitive Neuroscience top 1%
- Neural dynamics and brain function 13
- Visual perception and processing mechanisms 12
- Media Technology top 0.5%
- Biophysics top 2%
- Cell Image Analysis Techniques 7
- Advanced Fluorescence Microscopy Techniques 3
- Signal Processing top 5%
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- Radiomics and Machine Learning in Medical Imaging 6
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- AI in cancer detection 4
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- Prostate Cancer Treatment and Research 4
- Co-authors
- William BialekThomas W. CroninChuan‐Chin ChiaoJ. H. van HaterenDavid B. AgusKevin A. ArchieBartlett W. MelRajesh P. N. Rao
- Journals
- Network Computation in Neural Systems (4 papers)Scientific Reports (3 papers)Journal of the Optical Society of America A (3 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Daniel Ruderman
44 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Computer Vision and Pattern Recognition 1.5k
- Cognitive Neuroscience 1.3k
- Media Technology 567
- Biophysics 193
- Signal Processing 228
Countries citing papers authored by Daniel Ruderman
This map shows the geographic impact of Daniel Ruderman'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 Ruderman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Ruderman more than expected).
Fields of papers citing papers by Daniel Ruderman
This network shows the impact of papers produced by Daniel Ruderman. 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 Ruderman. The network helps show where Daniel Ruderman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel Ruderman, 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 | 2025 | 1 | |
| 2 | 2023 | 2 | |
| 3 | 2021 | 3 | |
| 4 | 2020 | 7 | |
| 5 | 2019 | 21 | |
| 6 | 2018 | 16 | |
| 7 | 2018 | 22 | |
| 8 | 2016 | 4 | |
| 9 | 2016 | 10 | |
| 10 | 2016 | 7 | |
| 11 | 2016 | 10 | |
| 12 | 2012 | 52 | |
| 13 | 2008 | 60 | |
| 14 | 2007 | 45 | |
| 15 | Statistics of cone responses to natural images : implications for visual coding | 1998 | 19 |
| 16 | Learning Lie Groups for Invariant Visual Perception | 1998 | 40 |
| 17 | Toward a Single-Cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your Dendrites | 1997 | 2 |
| 18 | Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation | 1996 | 3 |
| 19 | Statistics of Natural Images: Scaling in the Woods | 1993 | 15 |
| 20 | Optimal Sampling of Natural Images: A Design Principle for the Visual System | 1990 | 26 |
About Daniel Ruderman
Daniel Ruderman is a scholar working on Biophysics, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 44 papers that have together received 3.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (13 papers), Visual perception and processing mechanisms (12 papers), Cell Image Analysis Techniques (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (4 papers), Advanced Vision and Imaging (4 papers), Prostate Cancer Treatment and Research (4 papers) and Advanced Fluorescence Microscopy Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Cognitive Neuroscience (1.3k citations) and Media Technology (567 citations). Daniel Ruderman has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include William Bialek, Thomas W. Cronin, Chuan‐Chin Chiao, J. H. van Hateren, David B. Agus, Kevin A. Archie, Bartlett W. Mel, Rajesh P. N. Rao, Ali Madani and Nikhil Naik. Their work appears in journals such as Network Computation in Neural Systems, Scientific Reports, Journal of the Optical Society of America A, Journal of Thoracic Oncology and Cancer Research.
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.