Fred Hohman
Impact in
- Health Informatics top 5%
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- Scientific Computing and Data Management
Papers in
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- Data Visualization and Analytics 18
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- Anomaly Detection Techniques and Applications 5
- Explainable Artificial Intelligence (XAI) 4
- Data Stream Mining Techniques 3
- Adversarial Robustness in Machine Learning 2
- Advanced Text Analysis Techniques 2
- Co-authors
- Duen Horng Chau (12 shared papers)Steven M. Drucker (3 shared papers)Andrew Head (2 shared papers)Robert DeLine (2 shared papers)Nilaksh Das (3 shared papers)Kayur Patel (3 shared papers)Kanit Wongsuphasawat (3 shared papers)Zijie J. Wang (2 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (3 papers)Knowledge Discovery and Data Mining (1 paper)PubMed (2 papers)CHI Conference on Human Factors in Computing Systems (2 papers)View (1 paper)
- Partner nations
- United StatesGermanyNetherlands
In The Last Decade
Fred Hohman
24 papers receiving 839 citations
Peers
Comparison fields: 5 of 112
- Health Informatics 24
- Information Systems and Management 129
- Computer Vision and Pattern Recognition 340
- Artificial Intelligence 427
- Safety Research 81
Countries citing papers authored by Fred Hohman
This map shows the geographic impact of Fred Hohman'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 Fred Hohman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fred Hohman more than expected).
Fields of papers citing papers by Fred Hohman
This network shows the impact of papers produced by Fred Hohman. 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 Fred Hohman. The network helps show where Fred Hohman may publish in the future.
Co-authors
The 25 scholars most cited alongside Fred Hohman, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 189 | |
| 2 | 2019 | 136 | |
| 3 | 2019 | 100 | |
| 4 | 2020 | 84 | |
| 5 | 2018 | 77 | |
| 6 | 2022 | 49 | |
| 7 | 2022 | 37 | |
| 8 | 2017 | 30 | |
| 9 | 2020 | 26 | |
| 10 | 2019 | 24 | |
| 11 | 2017 | 20 | |
| 12 | 2024 | 12 | |
| 13 | 2018 | 12 | |
| 14 | 2017 | 11 | |
| 15 | 2023 | 9 | |
| 16 | 2023 | 8 | |
| 17 | 2020 | 8 | |
| 18 | Compression to the Rescue: Defending from Adversarial Attacks Across Modalities | 2018 | 7 |
| 19 | 2017 | 6 | |
| 20 | 2024 | 5 |
About Fred Hohman
Fred Hohman is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems and Management, Statistical and Nonlinear Physics and Molecular Biology, having authored 25 papers that have together received 857 indexed citations. Recurring topics across this work include Data Visualization and Analytics (18 papers), Scientific Computing and Data Management (7 papers), Anomaly Detection Techniques and Applications (5 papers), Complex Network Analysis Techniques (4 papers), Explainable Artificial Intelligence (XAI) (4 papers), Data Stream Mining Techniques (3 papers), Adversarial Robustness in Machine Learning (2 papers) and Advanced Text Analysis Techniques (2 papers). The work is most often cited by research in Health Informatics (24 citations), Information Systems and Management (129 citations), Computer Vision and Pattern Recognition (340 citations), Artificial Intelligence (427 citations) and Safety Research (81 citations). Fred Hohman has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Duen Horng Chau, Steven M. Drucker, Andrew Head, Robert DeLine, Nilaksh Das, Kayur Patel, Kanit Wongsuphasawat, Zijie J. Wang, Rich Caruana and Mary Beth Kery. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Knowledge Discovery and Data Mining, PubMed, CHI Conference on Human Factors in Computing Systems and View.
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.