Jonna Häkkilä

225 papers receiving 2.9k citations

Hit Papers

Lecture Notes in Computer Science (including subseries Le...20122026201620212012100200300400

Peers

Jonna Häkkilä
Comparison fields: 5 of 164
  • Human-Computer Interaction 1.8k
  • Computer Vision and Pattern Recognition 645
  • Cognitive Neuroscience 596
  • Social Psychology 389
  • Sociology and Political Science 322
Replace Hai‐Ning Liang with:
Hai‐Ning Liang China
Andreas Butz Germany
Giulio Jacucci Finland
Constantine Stephanidis Greece
Henry Been‐Lirn Duh Singapore
Matt Jones United Kingdom
Frank Vetere Australia
Marianna Obrist United Kingdom
Jesper Kjeldskov Denmark
Danaë Stanton Fraser United Kingdom
Jonna Häkkilä relative to Hai‐Ning Liang China Hai‐Ning Liang's profile →
Citations per field
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Hai‐Ning Liang · 1×
Citations per year

Countries citing papers authored by Jonna Häkkilä

Since Specialization
Citations

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

Fields of papers citing papers by Jonna Häkkilä

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonna Häkkilä

This figure shows the co-authorship network connecting the top 25 collaborators of Jonna Häkkilä. A scholar is included among the top collaborators of Jonna Häkkilä 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 Jonna Häkkilä. Jonna Häkkilä 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
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Arctic design for a sustainable, technological future
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On the road to digital paradise:the naked approach
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Graveyards as a Design Context for Unobtrusive Interaction
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)breakdown →
459
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Speech assisted mobile text entry
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Interaction in Location-Aware Messaging in a City Environment
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About Jonna Häkkilä

Jonna Häkkilä is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 241 papers that have together received 3.1k indexed citations. Recurring topics across this work include Interactive and Immersive Displays (120 papers), Innovative Human-Technology Interaction (105 papers) and Tactile and Sensory Interactions (48 papers). The work is most often cited by research in Human-Computer Interaction (1.8k citations), Computer Vision and Pattern Recognition (645 citations) and Cognitive Neuroscience (596 citations). Jonna Häkkilä has collaborated with scholars based in Finland, Germany and United States. Frequent co-authors include Ashley Colley, Jani Mäntyjärvi, Aaron Quigley, Edward Mutafungwa, Jukka Riekki, Heikki Ailisto, Nataša Milić-Frayling, Antti Evesti, Mika Rautiainen and Timo Korhonen. Their work appears in journals such as International Journal of Environmental Research and Public Health, Applied Sciences and International Journal of Human-Computer Studies.

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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