Gagan Bansal

1.5k citations
23 papers · 770 indexed · 1 hit paper · h-index 11

Gagan Bansal

22 papers receiving 741 citations

Hit Papers

Beyond Accuracy: The Role of Mental Models in Human-AI Te...2019202620212023201950100150200

Peers

Gagan Bansal
Comparison fields: 5 of 84
  • Artificial Intelligence 471
  • Safety Research 239
  • Social Psychology 159
  • Health Informatics 111
  • Information Systems 62
Replace Ashraf Abdul with:
Ashraf Abdul Singapore
Danding Wang China
Regina A. Pomranky United States
Dan Weld United States
Tongshuang Wu United States
Daniel Oster Germany
Beau G. Schelble United States
Joon Sung Park United States
Philipp Schmidt Germany
Shih‐Yi Chien United States
Gagan Bansal relative to Ashraf Abdul Singapore Ashraf Abdul's profile →
Citations per field
00.5×1.5×1.8×
Ashraf Abdul · 1×
Citations per year

Countries citing papers authored by Gagan Bansal

Since Specialization
Citations

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

Fields of papers citing papers by Gagan Bansal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gagan Bansal

This figure shows the co-authorship network connecting the top 25 collaborators of Gagan Bansal. A scholar is included among the top collaborators of Gagan Bansal 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 Gagan Bansal. Gagan Bansal 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 0
2 3
3 4
4 2
5 8
6 4
7 60
8 8
9 12
10 50
11
Beyond Accuracy: The Role of Mental Models in Human-AI Team Performancebreakdown →
239
12 19
13 77
14 2
15
Intelligible Artificial Intelligence
12
16 3
17 13
18 4
19 35
20 3

About Gagan Bansal

Gagan Bansal is a scholar working on Health Informatics, Safety Research and Management Information Systems, having authored 23 papers that have together received 770 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (11 papers), Ethics and Social Impacts of AI (9 papers) and Big Data and Business Intelligence (5 papers). The work is most often cited by research in Health Informatics (111 citations), Safety Research (239 citations) and Artificial Intelligence (471 citations). Gagan Bansal has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Daniel S. Weld, Eric Horvitz, Besmira Nushi, Ece Kamar, Walter S. Lasecki, Jennifer Wortman Vaughan, Q. Vera Liao, Valerie Chen, Mausam Mausam and Stephen Soderland. Their work appears in journals such as ACM Transactions on Computer-Human Interaction, Computers & Electrical Engineering and Proceedings of the ACM on Human-Computer Interaction.

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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