Zara Ambadar

24 papers receiving 4.4k citations

Hit Papers

The Extended Cohn-Kanade Dataset (CK+): A complete datase...2010202620152020201050010001.5k2.0k2.5k

Peers

Zara Ambadar
Comparison fields: 5 of 136
  • Experimental and Cognitive Psychology 3.1k
  • Computer Vision and Pattern Recognition 2.9k
  • Cognitive Neuroscience 1.1k
  • Social Psychology 682
  • Human-Computer Interaction 421
Replace Gwen Littlewort with:
Gwen Littlewort United States
Ian Fasel United States
Michel Valstar United Kingdom
Patrick Lucey United States
Jiro Gyoba Japan
Miyuki Kamachi Japan
Roland Goecke Australia
Hatice Güneş United Kingdom
Abhinav Dhall Australia
Mohammad Soleymani United States
Zara Ambadar relative to Gwen Littlewort United States Gwen Littlewort's profile →
Citations per field
00.5×3.5×
Gwen Littlewort · 1×
Citations per year

Countries citing papers authored by Zara Ambadar

Since Specialization
Citations

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

Fields of papers citing papers by Zara Ambadar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zara Ambadar

This figure shows the co-authorship network connecting the top 25 collaborators of Zara Ambadar. A scholar is included among the top collaborators of Zara Ambadar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zara Ambadar. Zara Ambadar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 25
2 30
3
The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expressionbreakdown →
2758
4 241
5 47
6
Improving Pain Recognition Through Better Utilisation of Temporal Information.
17
7 44
8 84
9 48
10 137
11 113
12 74
13 17
14 25
15 57
16 42
17 1
18 27
19 49
20
A Comparative Study of Alternative FACS Coding Algorithms
10

About Zara Ambadar

Zara Ambadar is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience and Pharmacy, having authored 24 papers that have together received 4.6k indexed citations. Recurring topics across this work include Face Recognition and Perception (12 papers), Face recognition and analysis (10 papers) and Emotion and Mood Recognition (9 papers). The work is most often cited by research in Experimental and Cognitive Psychology (3.1k citations), Computer Vision and Pattern Recognition (2.9k citations) and Human-Computer Interaction (421 citations). Zara Ambadar has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Jeffrey F. Cohn, Iain Matthews, Takeo Kanade, Patrick Lucey, Jason Saragih, Jonathan W. Schooler, Lawrence Ian Reed, Simon Lucey, Karen L. Schmidt and Ahmed Ashraf. Their work appears in journals such as Psychological Science, Journal of Experimental Psychology Human Perception & Performance and Emotion.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026