Stephen Macke
Impact in
- Software top 10%
- Software Reliability and Analysis Research
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- Scientific Computing and Data Management
Papers in ⓘ
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- Machine Learning and Data Classification 2
- Data Stream Mining Techniques 1
- Natural Language Processing Techniques 1
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- Software Engineering Techniques and Practices 2
- Software Engineering Research 2
- Co-authors
- Aditya Parameswaran (4 shared papers)Doris Xin (3 shared papers)Watts S. Humphrey (1 shared paper)Angela Lee (1 shared paper)Silu Huang (1 shared paper)Andrew Head (1 shared paper)Shreya Shankar (1 shared paper)Sarah Chasins (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (2 papers)Computer (1 paper)IEEE Data(base) Engineering Bulletin (1 paper)PubMed (1 paper)
- Partner nations
- United States
In The Last Decade
Stephen Macke
8 papers receiving 215 citations
Peers
Comparison fields: 5 of 63
- Software 33
- Information Systems and Management 33
- Health Informatics 6
- Management Information Systems 38
- Information Systems 94
Countries citing papers authored by Stephen Macke
This map shows the geographic impact of Stephen Macke'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 Stephen Macke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Macke more than expected).
Fields of papers citing papers by Stephen Macke
This network shows the impact of papers produced by Stephen Macke. 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 Stephen Macke. The network helps show where Stephen Macke may publish in the future.
Co-authors
The 15 scholars most cited alongside Stephen Macke, 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 | 2018 | 79 | |
| 2 | 1997 | 77 | |
| 3 | 2018 | 36 | |
| 4 | A Human-in-the-loop Perspective on AutoML: Milestones and the Road Ahead. | 2019 | 24 |
| 5 | 2022 | 10 | |
| 6 | 2012 | 6 | |
| 7 | 2018 | 3 | |
| 8 | 2002 | 2 |
About Stephen Macke
Stephen Macke is a scholar working on Artificial Intelligence, Information Systems, Information Systems and Management, Software and Computer Networks and Communications, having authored 8 papers that have together received 237 indexed citations. Recurring topics across this work include Scientific Computing and Data Management (3 papers), Software Testing and Debugging Techniques (2 papers), Machine Learning and Data Classification (2 papers), Software Engineering Techniques and Practices (2 papers), Software Engineering Research (2 papers), Data Stream Mining Techniques (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Software (33 citations), Information Systems and Management (33 citations), Health Informatics (6 citations), Management Information Systems (38 citations) and Information Systems (94 citations). Stephen Macke has collaborated with scholars based in United States. Frequent co-authors include Aditya Parameswaran, Doris Xin, Watts S. Humphrey, Angela Lee, Silu Huang, Andrew Head, Shreya Shankar, Sarah Chasins, Frank F. Xu and Aston Zhang. Their work appears in journals such as Proceedings of the VLDB Endowment, Computer, IEEE Data(base) Engineering Bulletin and PubMed.
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.