Michael Hind
- Hardware and Architecture top 0.5%
- Parallel Computing and Optimization Techniques 38
- Software top 0.5%
- Software Testing and Debugging Techniques 12
- Health Informatics top 1%
- Artificial Intelligence top 0.5%
- Logic, programming, and type systems 18
- Explainable Artificial Intelligence (XAI) 7
- Security and Verification in Computing 6
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- Distributed systems and fault tolerance 8
- Software System Performance and Reliability 8
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- Cloud Computing and Resource Management 11
- Co-authors
- David GroveMatthew ArnoldStephen J. FinkPeter F. SweeneyJong-Deok ChoiAmer DiwanMichael BurkeVivek Sarkar
- Journals
- ACM SIGPLAN Notices (10 papers)IBM Journal of Research and Development (3 papers)ACM Transactions on Programming Languages and Systems (3 papers)
- Partner nations
- United StatesNetherlandsBelgium
In The Last Decade
Michael Hind
59 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 106
- Hardware and Architecture 1.5k
- Software 646
- Health Informatics 118
- Artificial Intelligence 1.6k
- Computer Networks and Communications 1.1k
Countries citing papers authored by Michael Hind
This map shows the geographic impact of Michael Hind'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 Michael Hind with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Hind more than expected).
Fields of papers citing papers by Michael Hind
This network shows the impact of papers produced by Michael Hind. 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 Michael Hind. The network helps show where Michael Hind may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Hind, 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 | AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models | 2020 | 37 |
| 2 | 2019 | 52 | |
| 3 | Increasing Trust in AI Services through Supplier's Declarations of Conformity | 2018 | 17 |
| 4 | 2016 | 7 | |
| 5 | 2010 | 18 | |
| 6 | 2007 | 2 | |
| 7 | 2007 | 19 | |
| 8 | 2006 | 36 | |
| 9 | The Need for a Whole-System View of Performance. | 2005 | 0 |
| 10 | Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments | 2005 | 2 |
| 11 | 2003 | 21 | |
| 12 | 2003 | 0 | |
| 13 | 2002 | 3 | |
| 14 | 2002 | 0 | |
| 15 | 2001 | 380 | |
| 16 | 2000 | 40 | |
| 17 | 1999 | 196 | |
| 18 | 1995 | 10 | |
| 19 | 1995 | 4 | |
| 20 | 1992 | 1 |
About Michael Hind
Michael Hind is a scholar working on Hardware and Architecture, Software and Health Informatics, having authored 62 papers that have together received 3.0k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (38 papers), Logic, programming, and type systems (18 papers), Software Testing and Debugging Techniques (12 papers), Cloud Computing and Resource Management (11 papers), Distributed systems and fault tolerance (8 papers), Software System Performance and Reliability (8 papers), Explainable Artificial Intelligence (XAI) (7 papers) and Security and Verification in Computing (6 papers). The work is most often cited by research in Hardware and Architecture (1.5k citations), Software (646 citations) and Health Informatics (118 citations). Michael Hind has collaborated with scholars based in United States, Netherlands and Belgium. Frequent co-authors include David Grove, Matthew Arnold, Stephen J. Fink, Peter F. Sweeney, Jong-Deok Choi, Amer Diwan, Michael Burke, Vivek Sarkar, Paul Carini and Kush R. Varshney. Their work appears in journals such as ACM SIGPLAN Notices, IBM Journal of Research and Development, ACM Transactions on Programming Languages and Systems, Science of Computer Programming and IEEE Software.
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.