Elizabeth Cha

25 papers receiving 495 citations

Peers

Elizabeth Cha
Comparison fields: 5 of 83
  • Human-Computer Interaction 136
  • Social Psychology 216
  • Cognitive Neuroscience 115
  • Computer Science Applications 28
  • Control and Systems Engineering 102
Replace Elaine Schaertl Short with:
Elaine Schaertl Short United States
Rodolphe Gélin France
Naomi T. Fitter United States
Justin Hart United States
Rachel Gockley United States
Kerstin Severinson-Eklundh Sweden
Alireza Taheri Iran
Manja Lohse Netherlands
Michael Lankes Austria
Frank Broz United Kingdom
Elizabeth Cha relative to Elaine Schaertl Short United States Elaine Schaertl Short's profile →
Citations per field
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Citations per year

Countries citing papers authored by Elizabeth Cha

Since Specialization
Citations

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

Fields of papers citing papers by Elizabeth Cha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014103
2 201865
3 201542
4 201839
5 201735
6 202032
7 201628
8 201825
9 202018
10 201617
11 201517
12 201114
13 201112
14 202110
15 20189
16 20187
17 20176
18 20136
19 20175
20
Enabling Access to K-12 Education with Mobile Remote Presence
20164

About Elizabeth Cha

Elizabeth Cha is a scholar working on Social Psychology, Cognitive Neuroscience, Human-Computer Interaction, Artificial Intelligence and Control and Systems Engineering, having authored 27 papers that have together received 511 indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (9 papers), AI in Service Interactions (6 papers), Tactile and Sensory Interactions (5 papers), Virtual Reality Applications and Impacts (4 papers), Ethics and Social Impacts of AI (3 papers), Robotics and Automated Systems (2 papers), Action Observation and Synchronization (2 papers) and Child Development and Digital Technology (2 papers). The work is most often cited by research in Human-Computer Interaction (136 citations), Social Psychology (216 citations), Cognitive Neuroscience (115 citations), Computer Science Applications (28 citations) and Control and Systems Engineering (102 citations). Elizabeth Cha has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Maja J. Matarić, Terrence Fong, Siddhartha S Srinivasa, Naomi T. Fitter, Anca D. Dragan, Karlin Bark, Steven A. Jax, Laurel J. Buxbaum, Katherine J. Kuchenbecker and Leila Takayama. Their work appears in journals such as Facial Plastic Surgery & Aesthetic Medicine, IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Transactions on Haptics, IEEE Robotics and Automation Letters and The Laryngoscope.

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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