Alex Kale
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Visual perception and processing mechanisms
- Autism Spectrum Disorder Research
- Functional Brain Connectivity Studies
Papers in
-
- Data Visualization and Analytics 8
- Co-authors
- Jessica HullmanMatthew KayScott O. MurrayMichael‐Paul SchallmoMichael CorrellRaphael BernierRachel MillinTamar Kolodny
- Journals
- IEEE Transactions on Visualization and Computer Graphics (6 papers)Journal of Vision (2 papers)eLife (2 papers)Computer Graphics Forum (1 paper)Current Biology (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Alex Kale
17 papers receiving 452 citations
Peers
Comparison fields: 5 of 101
- Cognitive Neuroscience 183
- General Decision Sciences 17
- Computer Vision and Pattern Recognition 177
- Information Systems and Management 31
- Ecological Modeling 15
Countries citing papers authored by Alex Kale
This map shows the geographic impact of Alex Kale'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 Alex Kale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Kale more than expected).
Fields of papers citing papers by Alex Kale
This network shows the impact of papers produced by Alex Kale. 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 Alex Kale. The network helps show where Alex Kale may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Alex Kale, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 10 | |
| 5 | 2023 | 10 | |
| 6 | 2022 | 10 | |
| 7 | Visual Reasoning Strategies and Satisficing: How Uncertainty Visualization Design Impacts Effect Size Judgments and Decisions. | 2020 | 1 |
| 8 | 2020 | 29 | |
| 9 | 2020 | 35 | |
| 10 | 2019 | 11 | |
| 11 | 2019 | 12 | |
| 12 | 2019 | 23 | |
| 13 | 2018 | 39 | |
| 14 | 2018 | 13 | |
| 15 | 2018 | 68 | |
| 16 | 2018 | 103 | |
| 17 | 2018 | 43 | |
| 18 | 2018 | 1 | |
| 19 | 2018 | 45 | |
| 20 | 2016 | 4 |
About Alex Kale
Alex Kale is a scholar working on General Decision Sciences, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Sensory Systems, having authored 20 papers that have together received 457 indexed citations. Recurring topics across this work include Data Visualization and Analytics (8 papers), Neural dynamics and brain function (5 papers), Visual perception and processing mechanisms (5 papers), Retinal Development and Disorders (3 papers), Data Analysis with R (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Advanced Text Analysis Techniques (2 papers) and Color perception and design (2 papers). The work is most often cited by research in Cognitive Neuroscience (183 citations), General Decision Sciences (17 citations), Computer Vision and Pattern Recognition (177 citations), Information Systems and Management (31 citations) and Ecological Modeling (15 citations). Alex Kale has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Jessica Hullman, Matthew Kay, Scott O. Murray, Michael‐Paul Schallmo, Michael Correll, Raphael Bernier, Rachel Millin, Tamar Kolodny, Jeffrey Heer and Anastasia V. Flevaris. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Journal of Vision, eLife, Computer Graphics Forum and Current Biology.
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.