Sarah Mennicken
- Human-Computer Interaction top 2%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Software top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Elaine M. HuangJo VermeulenJiyun LeeMichael L. LittmanBlase UrJennifer S. ThomDavid KimAsta Roseway
- Topics
- Innovative Human-Technology Interaction (7 papers)Context-Aware Activity Recognition Systems (5 papers)Mobile Crowdsensing and Crowdsourcing (4 papers)
- Journals
- Proceedings of the ACM on Human-Computer InteractionZurich Open Repository and Archive (University of Zurich)National Conference on Artificial Intelligence
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Sarah Mennicken
22 papers receiving 450 citations
Peers
Comparison fields: 5 of 65
- Human-Computer Interaction 174
- Computer Vision and Pattern Recognition 156
- Electrical and Electronic Engineering 103
- Software 98
- Computer Networks and Communications 88
Countries citing papers authored by Sarah Mennicken
This map shows the geographic impact of Sarah Mennicken'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 Sarah Mennicken with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sarah Mennicken more than expected).
Fields of papers citing papers by Sarah Mennicken
This network shows the impact of papers produced by Sarah Mennicken. 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 Sarah Mennicken. The network helps show where Sarah Mennicken may publish in the future.
Co-authorship network of co-authors of Sarah Mennicken
This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Mennicken. A scholar is included among the top collaborators of Sarah Mennicken based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sarah Mennicken. Sarah Mennicken is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 6 | |
| 3 | 1 | |
| 4 | 16 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | Challenges and Methods in Design of Domain-specific Voice Assistants. | 3 |
| 8 | 31 | |
| 9 | 153 | |
| 10 | 31 | |
| 11 | 128 | |
| 12 | 14 | |
| 13 | 13 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 1 | |
| 18 | 4 | |
| 19 | 11 | |
| 20 | 15 |
About Sarah Mennicken
Sarah Mennicken is a scholar working on Human-Computer Interaction, Computer Science Applications and Health Information Management, having authored 22 papers that have together received 470 indexed citations. Recurring topics across this work include Innovative Human-Technology Interaction (7 papers), Context-Aware Activity Recognition Systems (5 papers) and Mobile Crowdsensing and Crowdsourcing (4 papers). The work is most often cited by research in Human-Computer Interaction (174 citations), Software (98 citations) and Computer Science Applications (67 citations). Sarah Mennicken has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Elaine M. Huang, Jo Vermeulen, Jiyun Lee, Michael L. Littman, Blase Ur, Jennifer S. Thom, David Kim, Asta Roseway, A. J. Bernheim Brush and Martina Ziefle. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Zurich Open Repository and Archive (University of Zurich) and National Conference on Artificial Intelligence.
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.