Jonas Schild

935 citations
47 papers · 608 · h-index 13

Impact in

Papers in

Jonas Schild

45 papers receiving 578 citations

Peers

Jonas Schild
Comparison fields: 5 of 94
  • Human-Computer Interaction 352
  • Computer Vision and Pattern Recognition 189
  • Media Technology 65
  • Neuropsychology and Physiological Psychology 11
  • Developmental and Educational Psychology 85
Replace Wenge Xu with:
Wenge Xu China
Cali Fidopiastis United States
Eunhee Chang South Korea
Ancrêt Szpak Australia
Katja Rogers Germany
Rubén García Spain
Edmund LoPresti United States
Polona Caserman Germany
Leonardo Angelini Switzerland
Mungyeong Choe South Korea
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Citations per field
00.5×4.2×
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Citations per year

Countries citing papers authored by Jonas Schild

Since Specialization
Citations

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

Fields of papers citing papers by Jonas Schild

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201098
2 202074
3 201260
4 201842
5 201841
6 201829
7 201728
8 201020
9 201220
10 201315
11 201615
12
Exergaming for Elderly Persons: Analyzing Player Experience and Performance
201113
13 201412
14 201710
15 202110
16 20158
17 20168
18 20218
19 20098
20 20197

About Jonas Schild

Jonas Schild is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Media Technology, Social Psychology and Cognitive Neuroscience, having authored 47 papers that have together received 608 indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (29 papers), Advanced Optical Imaging Technologies (10 papers), Augmented Reality Applications (10 papers), Interactive and Immersive Displays (7 papers), Simulation-Based Education in Healthcare (5 papers), Color perception and design (4 papers), Computer Graphics and Visualization Techniques (4 papers) and Educational Games and Gamification (4 papers). The work is most often cited by research in Human-Computer Interaction (352 citations), Computer Vision and Pattern Recognition (189 citations), Media Technology (65 citations), Neuropsychology and Physiological Psychology (11 citations) and Developmental and Educational Psychology (85 citations). Jonas Schild has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Maic Masuch, Kathrin Gerling, Joseph J. LaViola, Thomas Luiz, Stefan Mohr, Guillermo Carbonell, Rainer Herpers, Arun K. Kulshreshth, Robert Walter and Alexander Marquardt. Their work appears in journals such as The Visual Computer, JMIR Serious Games, Environmental Research Letters, Frontiers in Education and 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW).

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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