Patrick Albus

16 papers receiving 562 citations

Patrick Albus's Hit Papers

Signaling in virtual reality influences learning outcome and cognitive load 2021 · 235 citations
2350+1+3Years since publication50100150200

Peers

Patrick Albus
Comparison fields: 5 of 72
  • Human-Computer Interaction 218
  • Experimental and Cognitive Psychology 117
  • Automotive Engineering 92
  • Developmental and Educational Psychology 93
  • Computer Vision and Pattern Recognition 96
Replace Fangtian Ying with:
Fangtian Ying China
Vijayakumar Nanjappan Finland
Aske Mottelson Denmark
Jack McKechnie United Kingdom
David E Hamilton United Kingdom
Margarita Anastassova France
Wei-Kai Liou Taiwan
Andrea Brogni Italy
Samantha L. Finkelstein United States
Gayathri Narasimham United States
Patrick Albus relative to Fangtian Ying China Fangtian Ying's profile →
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Fangtian Ying · 1×
Citations per year

Countries citing papers authored by Patrick Albus

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Albus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1
Signaling in virtual reality influences learning outcome and cognitive load
Hit paper breakdown →
2021235
2 202263
3 202057
4 202147
5 200835
6 201930
7 202126
8 202325
9 202123
10 202217
11 20255
12 20054
13 20224
14 20243
15 20202
16 20081
17 20010

About Patrick Albus

Patrick Albus is a scholar working on Human-Computer Interaction, Experimental and Cognitive Psychology, Automotive Engineering, Mechanical Engineering and Developmental and Educational Psychology, having authored 17 papers that have together received 577 indexed citations. Recurring topics across this work include Visual and Cognitive Learning Processes (7 papers), Virtual Reality Applications and Impacts (7 papers), Additive Manufacturing Materials and Processes (4 papers), Spatial Cognition and Navigation (3 papers), High Entropy Alloys Studies (3 papers), Additive Manufacturing and 3D Printing Technologies (2 papers), Data Visualization and Analytics (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Human-Computer Interaction (218 citations), Experimental and Cognitive Psychology (117 citations), Automotive Engineering (92 citations), Developmental and Educational Psychology (93 citations) and Computer Vision and Pattern Recognition (96 citations). Patrick Albus has collaborated with scholars based in Germany and China. Frequent co-authors include Tina Seufert, Andrea Vogt, Harald Baumeister, Ingomar Kelbassa, Jens B. Dietrich, David Daniel Ebert, Ann‐Marie Küchler, Michael Rietzler, Enrico Rukzio and Andrés Gasser. Their work appears in journals such as Optics & Laser Technology, BMJ Open, Internet Interventions, Frontiers in Psychology and Scientific Reports.

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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