Gabriel P. Haas
- Pulmonary and Respiratory Medicine top 0.5%
- Prostate Cancer Treatment and Research 64
- Prostate Cancer Diagnosis and Treatment 48
- Urology top 1%
- Rheumatology top 0.5%
- Urologic and reproductive health conditions 18
- Cancer Research top 2%
- Cancer, Lipids, and Metabolism 16
- Oncology top 2%
- Cancer Immunotherapy and Biomarkers 23
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- Bladder and Urothelial Cancer Treatments 26
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- Immunotherapy and Immune Responses 23
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- Radiopharmaceutical Chemistry and Applications 19
- Co-authors
- Wael SakrJohn D. CrissmanJ. Edson PontesChing Y. WangNicolas Barry DelongchampsDavid J. GrignonGustavo de la RozaGilda G. Hillman
- Journals
- New England Journal of Medicine (2 papers)Journal of Clinical Investigation (1 paper)The Journal of Experimental Medicine (1 paper)
- Partner nations
- United StatesFranceJapan
In The Last Decade
Gabriel P. Haas
161 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 142
- Pulmonary and Respiratory Medicine 3.3k
- Urology 448
- Rheumatology 1.0k
- Cancer Research 729
- Oncology 1.3k
Countries citing papers authored by Gabriel P. Haas
This map shows the geographic impact of Gabriel P. Haas'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 Gabriel P. Haas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel P. Haas more than expected).
Fields of papers citing papers by Gabriel P. Haas
This network shows the impact of papers produced by Gabriel P. Haas. 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 Gabriel P. Haas. The network helps show where Gabriel P. Haas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gabriel P. Haas, 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 | 2024 | 4 | |
| 3 | Exploiting Directly-Attached NVMe Arrays in DBMS. | 2020 | 5 |
| 4 | 2013 | 2 | |
| 5 | 2012 | 15 | |
| 6 | 2009 | 30 | |
| 7 | 2008 | 8 | |
| 8 | 2005 | 39 | |
| 9 | 2002 | 12 | |
| 10 | 2000 | 13 | |
| 11 | 2000 | 30 | |
| 12 | 1997 | 10 | |
| 13 | 1995 | 40 | |
| 14 | 1995 | 52 | |
| 15 | 1995 | 91 | |
| 16 | 1995 | 1 | |
| 17 | 1993 | 153 | |
| 18 | 1993 | 5 | |
| 19 | 1993 | 16 | |
| 20 | 1978 | 18 |
About Gabriel P. Haas
Gabriel P. Haas is a scholar working on Pulmonary and Respiratory Medicine, Rheumatology and Oncology, having authored 167 papers that have together received 5.8k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (64 papers), Prostate Cancer Diagnosis and Treatment (48 papers), Bladder and Urothelial Cancer Treatments (26 papers), Cancer Immunotherapy and Biomarkers (23 papers), Immunotherapy and Immune Responses (23 papers), Radiopharmaceutical Chemistry and Applications (19 papers), Urologic and reproductive health conditions (18 papers) and Cancer, Lipids, and Metabolism (16 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (3.3k citations), Urology (448 citations) and Rheumatology (1.0k citations). Gabriel P. Haas has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Wael Sakr, John D. Crissman, J. Edson Pontes, Ching Y. Wang, Nicolas Barry Delongchamps, David J. Grignon, Gustavo de la Roza, Gilda G. Hillman, Peter Haas and Steve Landas. Their work appears in journals such as New England Journal of Medicine, Journal of Clinical Investigation and The Journal of Experimental Medicine.
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.