Matthew L. Lee
- Human-Computer Interaction top 5%
- Innovative Human-Technology Interaction 4
- Health Informatics top 10%
- Applied Psychology top 10%
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- Personal Information Management and User Behavior 2
- Demography top 10%
- Technology Use by Older Adults 5
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- Context-Aware Activity Recognition Systems 7
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- Explainable Artificial Intelligence (XAI) 3
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- Ethics and Social Impacts of AI 3
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- Dementia and Cognitive Impairment Research 2
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- Cardiac Arrest and Resuscitation 2
- Co-authors
- Anind K. DeyScott L. CarterDaniel AvrahamiQiaoning ZhangHeather FaucettVincent W.-S. TsengLaurent DenoueJeffrey Marlow
- Journals
- The American Surgeon (2 papers)Proceedings of the ACM on Human-Computer Interaction (1 paper)CHI Conference on Human Factors in Computing Systems (1 paper)
- Partner nations
- United StatesJapanCanada
In The Last Decade
Matthew L. Lee
19 papers receiving 345 citations
Peers
Comparison fields: 5 of 79
- Human-Computer Interaction 113
- Health Informatics 15
- Applied Psychology 46
- Information Systems and Management 39
- Demography 64
Countries citing papers authored by Matthew L. Lee
This map shows the geographic impact of Matthew L. Lee'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 Matthew L. Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew L. Lee more than expected).
Fields of papers citing papers by Matthew L. Lee
This network shows the impact of papers produced by Matthew L. Lee. 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 Matthew L. Lee. The network helps show where Matthew L. Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Matthew L. Lee, 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 | 2024 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 7 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 1 | |
| 8 | 2022 | 47 | |
| 9 | 2020 | 1 | |
| 10 | 2020 | 4 | |
| 11 | 2020 | 11 | |
| 12 | 2019 | 41 | |
| 13 | 2017 | 41 | |
| 14 | 2017 | 44 | |
| 15 | Task-based embedded assessment of functional abilities for aging in place | 2012 | 3 |
| 16 | 2011 | 54 | |
| 17 | 2010 | 26 | |
| 18 | 2010 | 4 | |
| 19 | 2010 | 5 | |
| 20 | 2007 | 59 |
About Matthew L. Lee
Matthew L. Lee is a scholar working on Health Informatics, Human-Computer Interaction and Demography, having authored 20 papers that have together received 355 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (7 papers), Technology Use by Older Adults (5 papers), Innovative Human-Technology Interaction (4 papers), Explainable Artificial Intelligence (XAI) (3 papers), Ethics and Social Impacts of AI (3 papers), Personal Information Management and User Behavior (2 papers), Dementia and Cognitive Impairment Research (2 papers) and Cardiac Arrest and Resuscitation (2 papers). The work is most often cited by research in Human-Computer Interaction (113 citations), Health Informatics (15 citations) and Applied Psychology (46 citations). Matthew L. Lee has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Anind K. Dey, Scott L. Carter, Daniel Avrahami, Anind K. Dey, Qiaoning Zhang, Heather Faucett, Vincent W.-S. Tseng, Laurent Denoue, Jeffrey Marlow and Kristin Williams. Their work appears in journals such as The American Surgeon, Proceedings of the ACM on Human-Computer Interaction and CHI Conference on Human Factors in Computing Systems.
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.