Peter Chin
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- Multiple Sclerosis Research Studies 23
- Neurology top 5%
- Peripheral Neuropathies and Disorders 4
- Rheumatology top 5%
- Rheumatoid Arthritis Research and Therapies 4
- Immunology top 10%
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- Polyomavirus and related diseases 5
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- Monoclonal and Polyclonal Antibodies Research 4
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- Sparse and Compressive Sensing Techniques 3
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- Adversarial Robustness in Machine Learning 3
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- Topological and Geometric Data Analysis 3
- Co-authors
- Seymour M. AntelmanHenry SzechtmanAlan E. FisherStephen L. HauserPeter A. CalabresiJiameng ZhangCraig H. SmithPaul O’Connor
- Journals
- Neurology (22 papers)Journal of Neurology Neurosurgery & Psychiatry (2 papers)IEEE Transactions on Biomedical Circuits and Systems (2 papers)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Peter Chin
59 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Pathology and Forensic Medicine 821
- Neurology 375
- Cellular and Molecular Neuroscience 279
- Rheumatology 212
- Immunology 255
Countries citing papers authored by Peter Chin
This map shows the geographic impact of Peter Chin'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 Peter Chin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Chin more than expected).
Fields of papers citing papers by Peter Chin
This network shows the impact of papers produced by Peter Chin. 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 Peter Chin. The network helps show where Peter Chin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter Chin, 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 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 0 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 5 | |
| 8 | Tree Structured Multimedia Signal Modeling. | 2018 | 1 |
| 9 | Learning to Repair Software Vulnerabilities with Generative Adversarial Networks | 2018 | 5 |
| 10 | 2017 | 1 | |
| 11 | 2016 | 1 | |
| 12 | 2016 | 12 | |
| 13 | 2016 | 24 | |
| 14 | 2015 | 2 | |
| 15 | 2014 | 9 | |
| 16 | 2014 | 8 | |
| 17 | 2014 | 1 | |
| 18 | 2013 | 2 | |
| 19 | 2013 | 1 | |
| 20 | Rituximab in patients with primary progressive multiple sclerosis: Results of a randomized double‐blind placebo‐controlled multicenter trialbreakdown → | 2009 | 686 |
About Peter Chin
Peter Chin is a scholar working on Pathology and Forensic Medicine, Signal Processing and Rheumatology, having authored 67 papers that have together received 1.7k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (23 papers), Polyomavirus and related diseases (5 papers), Peripheral Neuropathies and Disorders (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Rheumatoid Arthritis Research and Therapies (4 papers), Sparse and Compressive Sensing Techniques (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Topological and Geometric Data Analysis (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (821 citations), Neurology (375 citations) and Cellular and Molecular Neuroscience (279 citations). Peter Chin has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Seymour M. Antelman, Henry Szechtman, Alan E. Fisher, Stephen L. Hauser, Peter A. Calabresi, Jiameng Zhang, Craig H. Smith, Paul O’Connor, Emmanuelle Waubant and Hillel Panitch. Their work appears in journals such as Neurology, Journal of Neurology Neurosurgery & Psychiatry, IEEE Transactions on Biomedical Circuits and Systems, The Journal of Urology and Annals of Neurology.
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.