Daniel Saakes

1.0k citations
61 papers · 694 · h-index 15

Impact in

Papers in

Daniel Saakes

58 papers receiving 655 citations

Peers

Daniel Saakes
Comparison fields: 5 of 97
  • Human-Computer Interaction 320
  • Sensory Systems 50
  • Computer Vision and Pattern Recognition 196
  • Social Psychology 192
  • Experimental and Cognitive Psychology 88
Replace Itiro Siio with:
Itiro Siio Japan
Richard Skarbez Australia
Umberto Cugini Italy
Marino Menozzi Switzerland
Jorge Alcaide-Marzal Spain
Yomna Abdelrahman Germany
Giandomenico Caruso Italy
Pascal Knierim Germany
Olivier Christmann France
Huong Quynh Dinh United States
Daniel Saakes relative to Itiro Siio Japan Itiro Siio's profile →
Citations per field
00.5×3.2×
Itiro Siio · 1×
Citations per year

Countries citing papers authored by Daniel Saakes

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Saakes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Saakes, 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 Saakes Line = papers co-authored together Daniel Saakes links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202199
2 201645
3 200543
4 201333
5 201633
6 201830
7 201328
8 201825
9 201924
10 200721
11 201219
12 201918
13 201618
14 201918
15 201816
16 202114
17 201412
18 201711
19 200911
20 201010

About Daniel Saakes

Daniel Saakes is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Social Psychology, Mechanical Engineering and Automotive Engineering, having authored 61 papers that have together received 694 indexed citations. Recurring topics across this work include Interactive and Immersive Displays (23 papers), Augmented Reality Applications (14 papers), Virtual Reality Applications and Impacts (12 papers), Innovative Human-Technology Interaction (12 papers), Additive Manufacturing and 3D Printing Technologies (8 papers), Tactile and Sensory Interactions (7 papers), Color perception and design (7 papers) and Ergonomics and Musculoskeletal Disorders (6 papers). The work is most often cited by research in Human-Computer Interaction (320 citations), Sensory Systems (50 citations), Computer Vision and Pattern Recognition (196 citations), Social Psychology (192 citations) and Experimental and Cognitive Psychology (88 citations). Daniel Saakes has collaborated with scholars based in South Korea, Netherlands and Japan. Frequent co-authors include Thomas J. L. van Rompay, Woojoo Kim, Chunxi Huang, Shuping Xiong, Thomas van Rompay, Masahiko İnami, Paul Hekkert, Takeo Igarashi, Anna Fenko and Alexander Plopski. Their work appears in journals such as Food Quality and Preference, European Journal of Mechanics - A/Solids, Advanced Engineering Materials, Personal and Ubiquitous Computing and Proceedings of the ACM on Human-Computer Interaction.

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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