Gagan Bansal

1.5k total citations · 1 hit paper
23 papers, 770 citations indexed

About

Gagan Bansal is a scholar working on Artificial Intelligence, Safety Research and Management Information Systems. According to data from OpenAlex, Gagan Bansal has authored 23 papers receiving a total of 770 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 9 papers in Safety Research and 5 papers in Management Information Systems. Recurrent topics in Gagan Bansal's work include Explainable Artificial Intelligence (XAI) (11 papers), Ethics and Social Impacts of AI (9 papers) and Big Data and Business Intelligence (5 papers). Gagan Bansal is often cited by papers focused on Explainable Artificial Intelligence (XAI) (11 papers), Ethics and Social Impacts of AI (9 papers) and Big Data and Business Intelligence (5 papers). Gagan Bansal collaborates with scholars based in United States, United Kingdom and India. Gagan Bansal's 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 Adam Fourney and has published in prestigious journals such as ACM Transactions on Computer-Human Interaction, Computers & Electrical Engineering and Proceedings of the ACM on Human-Computer Interaction.

In The Last Decade

Gagan Bansal

22 papers receiving 741 citations

Hit Papers

Beyond Accuracy: The Role... 2019 2026 2021 2023 2019 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance
    2019 239 citations Gagan Bansal, Besmira Nushi et al. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gagan Bansal United States 11 471 239 159 111 62 23 770
Ashraf Abdul Singapore 6 657 1.4× 304 1.3× 90 0.6× 173 1.6× 99 1.6× 7 956
Dan Weld United States 6 450 1.0× 223 0.9× 161 1.0× 96 0.9× 109 1.8× 6 973
Stephanie Houde United States 10 384 0.8× 313 1.3× 46 0.3× 122 1.1× 94 1.5× 24 829
Danding Wang China 8 698 1.5× 290 1.2× 91 0.6× 173 1.6× 151 2.4× 18 1.0k
Tongshuang Wu United States 17 608 1.3× 93 0.4× 63 0.4× 58 0.5× 133 2.1× 48 971
Daniel Oster Germany 10 279 0.6× 131 0.5× 59 0.4× 85 0.8× 48 0.8× 18 537
Regina A. Pomranky United States 3 186 0.4× 162 0.7× 498 3.1× 51 0.5× 45 0.7× 7 768
Kuntal Dey India 15 638 1.4× 311 1.3× 35 0.2× 88 0.8× 175 2.8× 54 1.1k
J.D. Zamfirescu-Pereira United States 9 266 0.6× 49 0.2× 61 0.4× 53 0.5× 90 1.5× 22 578
Shivani Kapania United States 8 233 0.5× 172 0.7× 18 0.1× 61 0.5× 77 1.2× 14 610

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
1.
2.
Bansal, Gagan, et al.. (2025). Interactive Debugging and Steering of Multi-Agent AI Systems. ArXiv.org. 1–15. 3 indexed citations
3.
Bansal, Gagan, et al.. (2024). Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions. ACM Transactions on Computer-Human Interaction. 4 indexed citations
4.
Ashktorab, Zahra, Gagan Bansal, Zana Buçinca, et al.. (2024). Trust and Reliance in Evolving Human-AI Workflows (TREW). 1–6. 2 indexed citations
5.
Bansal, Gagan, et al.. (2024). Automatic number plate detection and recognition using YOLO world. Computers & Electrical Engineering. 120. 109646–109646. 8 indexed citations
6.
Bansal, Gagan, Zana Buçinca, Kenneth Holstein, et al.. (2023). Workshop on Trust and Reliance in AI-Human Teams (TRAIT). 1–6. 4 indexed citations
7.
Bansal, Gagan, Alison Smith, Zana Buçinca, et al.. (2022). Workshop on Trust and Reliance in AI-Human Teams (TRAIT). CHI Conference on Human Factors in Computing Systems Extended Abstracts. 1–6. 8 indexed citations
8.
9.
Bansal, Gagan, Besmira Nushi, Ece Kamar, Eric Horvitz, & Daniel S. Weld. (2021). Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork. Proceedings of the AAAI Conference on Artificial Intelligence. 35(13). 11405–11414. 50 indexed citations
10.
Bansal, Gagan, Besmira Nushi, Ece Kamar, Eric Horvitz, & Daniel S. Weld. (2020). Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork. arXiv (Cornell University). 35(13). 11405–11414. 1 indexed citations
11.
Ramos, Gonzalo, Jina Suh, Christopher Meek, et al.. (2019). Emerging Perspectives in Human-Centered Machine Learning. 1–8. 19 indexed citations
12.
Bansal, Gagan, Besmira Nushi, Ece Kamar, et al.. (2019). Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 7. 2–11. 239 indexed citations breakdown →
13.
Chen, Mia Xu, Gagan Bansal, Yuan Cao, et al.. (2019). Gmail Smart Compose. 2287–2295. 77 indexed citations
14.
Weld, Daniel S. & Gagan Bansal. (2018). Intelligible Artificial Intelligence. 12 indexed citations
15.
Bansal, Gagan. (2018). Explanatory Dialogs. 356–357. 2 indexed citations
16.
Bansal, Gagan & Daniel S. Weld. (2018). A Coverage-Based Utility Model for Identifying Unknown Unknowns. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 13 indexed citations
17.
Bansal, Gagan, et al.. (2018). Secure and Automated Enterprise Revenue Forecasting. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 3 indexed citations
18.
Bansal, Gagan, et al.. (2018). Moedor Cleaning Robot. 4. 1–5. 4 indexed citations
19.
Christensen, Janara, Stephen Soderland, Gagan Bansal, & Mausam Mausam. (2014). Hierarchical Summarization: Scaling Up Multi-Document Summarization. 902–912. 35 indexed citations
20.
Chen, X. Chelsea, et al.. (2014). Online Discovery of Group Level Events in Time Series. 632–640. 3 indexed citations

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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