Daniel Buschek

3.8k citations
89 papers · 1.6k · h-index 21

Impact in

Papers in

Daniel Buschek

83 papers receiving 1.6k citations

Peers

Daniel Buschek
Comparison fields: 5 of 103
  • Human-Computer Interaction 705
  • Health Informatics 50
  • Applied Psychology 124
  • Signal Processing 167
  • Information Systems 339
Replace Massimo Zancanaro with:
Massimo Zancanaro Italy
Michael McTear United Kingdom
Jo Vermeulen Belgium
Daniel Avrahami United States
Adam Fourney United States
Andreas Sonderegger Switzerland
Jerry Alan Fails United States
Cosmin Munteanu Canada
Daniel Gonçalves Portugal
Silvia Gabrielli Italy
Daniel Buschek relative to Massimo Zancanaro Italy Massimo Zancanaro's profile →
Citations per field
00.5×2.6×
Massimo Zancanaro · 1×
Citations per year

Countries citing papers authored by Daniel Buschek

Since Specialization
Citations

This map shows the geographic impact of Daniel Buschek'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 Daniel Buschek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Buschek more than expected).

Fields of papers citing papers by Daniel Buschek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Buschek. 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 Daniel Buschek. The network helps show where Daniel Buschek may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Buschek, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Buschek Line = papers co-authored together Daniel Buschek links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020159
2 2019154
3 2017100
4 201592
5 201788
6 201975
7 201975
8 202373
9 201957
10 201856
11 201840
12 201940
13 202436
14 201932
15 201532
16 201830
17 202028
18 201624
19 202124
20 201823

About Daniel Buschek

Daniel Buschek is a scholar working on Human-Computer Interaction, Sociology and Political Science, Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 89 papers that have together received 1.6k indexed citations. Recurring topics across this work include Innovative Human-Technology Interaction (25 papers), Interactive and Immersive Displays (23 papers), User Authentication and Security Systems (12 papers), Data Visualization and Analytics (9 papers), Human-Automation Interaction and Safety (9 papers), Gaze Tracking and Assistive Technology (9 papers), Personal Information Management and User Behavior (9 papers) and Usability and User Interface Design (9 papers). The work is most often cited by research in Human-Computer Interaction (705 citations), Health Informatics (50 citations), Applied Psychology (124 citations), Signal Processing (167 citations) and Information Systems (339 citations). Daniel Buschek has collaborated with scholars based in Germany, United States and Finland. Frequent co-authors include Florian Alt, Heinrich Hußmann, Alexander De Luca, Mariam Hassib, Malin Eiband, Lukas Mecke, Sarah Theres Völkel, Paweł W. Woźniak, Sylvia Rothe and Sarah Prange. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Proceedings of the ACM on Human-Computer Interaction, ACM Transactions on Computer-Human Interaction, Virtual Reality and Proceedings of the National Academy of Sciences.

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.

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