Sam Blackman
Impact in
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- Target Tracking and Data Fusion in Sensor Networks
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- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
Papers in
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- Target Tracking and Data Fusion in Sensor Networks 3
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- Melanoma and MAPK Pathways 2
- Co-authors
- R.J. Fitzgerald (1 shared paper)Yaakov Bar‐Shalom (1 shared paper)David S. Hong (1 shared paper)Gregory Lizée (1 shared paper)Laszlo Radvanyi (1 shared paper)Luis M. Vence (1 shared paper)Vicki Goodman (1 shared paper)Patrick Hwu (1 shared paper)
- Journals
- Clinical Cancer Research (1 paper)IEEE Transactions on Aerospace and Electronic Systems (1 paper)Cancer Research (1 paper)Heliyon (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)
- Partner nations
- United StatesNetherlands
In The Last Decade
Sam Blackman
7 papers receiving 184 citations
Peers
Comparison fields: 5 of 51
- Artificial Intelligence 81
- Oncology 57
- Aerospace Engineering 44
- Immunology 29
- Signal Processing 14
Countries citing papers authored by Sam Blackman
This map shows the geographic impact of Sam Blackman'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 Sam Blackman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Blackman more than expected).
Fields of papers citing papers by Sam Blackman
This network shows the impact of papers produced by Sam Blackman. 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 Sam Blackman. The network helps show where Sam Blackman may publish in the future.
Co-authors
The 20 scholars most cited alongside Sam Blackman, 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 | 2012 | 82 | |
| 2 | 2007 | 82 | |
| 3 | 2010 | 13 | |
| 4 | Optimal allocation of multi-platform sensor resources for multiple target tracking | 2011 | 4 |
| 5 | On the application of multiple hypothesis tracking to the cyber domain | 2011 | 3 |
| 6 | 2021 | 3 | |
| 7 | 2021 | 2 |
About Sam Blackman
Sam Blackman is a scholar working on Artificial Intelligence, Molecular Biology, Signal Processing, Aerospace Engineering and Computer Networks and Communications, having authored 7 papers that have together received 189 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (3 papers), Melanoma and MAPK Pathways (2 papers), Military Defense Systems Analysis (1 paper), Guidance and Control Systems (1 paper), Radar Systems and Signal Processing (1 paper), Advanced Statistical Methods and Models (1 paper), Fault Detection and Control Systems (1 paper) and Ocular Oncology and Treatments (1 paper). The work is most often cited by research in Artificial Intelligence (81 citations), Oncology (57 citations), Aerospace Engineering (44 citations), Immunology (29 citations) and Signal Processing (14 citations). Sam Blackman has collaborated with scholars based in United States and Netherlands. Frequent co-authors include R.J. Fitzgerald, Yaakov Bar‐Shalom, David S. Hong, Gregory Lizée, Laszlo Radvanyi, Luis M. Vence, Vicki Goodman, Patrick Hwu, Gerald S. Falchook and Chengwen Liu. Their work appears in journals such as Clinical Cancer Research, IEEE Transactions on Aerospace and Electronic Systems, Cancer Research, Heliyon and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.