Advait Sarkar

1.5k total citations · 2 hit papers
50 papers, 581 citations indexed

About

Advait Sarkar is a scholar working on Artificial Intelligence, Software and Statistics and Probability. According to data from OpenAlex, Advait Sarkar has authored 50 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 16 papers in Software and 11 papers in Statistics and Probability. Recurrent topics in Advait Sarkar's work include Spreadsheets and End-User Computing (16 papers), Statistics Education and Methodologies (11 papers) and Data Visualization and Analytics (6 papers). Advait Sarkar is often cited by papers focused on Spreadsheets and End-User Computing (16 papers), Statistics Education and Methodologies (11 papers) and Data Visualization and Analytics (6 papers). Advait Sarkar collaborates with scholars based in United Kingdom, United States and Netherlands. Advait Sarkar's co-authors include Sean Rintel, Ioannis Politis, Charlie Hewitt, Lev Tankelevitch, Abigail Sellen, Cecilia Mascolo, Neal Lathia, Andrew D. Gordon, Ian Drosos and Alan F. Blackwell and has published in prestigious journals such as Communications of the ACM, Disability and Rehabilitation and Transportation.

In The Last Decade

Advait Sarkar

46 papers receiving 563 citations

Hit Papers

The Metacognitive Demands and Opportunities of Generative AI 2024 2026 2025 2024 2025 20 40 60
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. The Metacognitive Demands and Opportunities of Generative AI
    2024 71 citations Lev Tankelevitch, Advait Sarkar et al. profile →
  2. The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers
    2025 64 citations Advait Sarkar, Lev Tankelevitch et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Advait Sarkar United Kingdom 13 133 128 85 82 73 50 581
Norman G. Vinson Canada 11 88 0.7× 97 0.8× 42 0.5× 111 1.4× 148 2.0× 22 798
Peter Johnson United Kingdom 15 202 1.5× 161 1.3× 62 0.7× 55 0.7× 13 0.2× 48 895
Thomas O. Meservy United States 14 138 1.0× 210 1.6× 31 0.4× 26 0.3× 10 0.1× 45 738
Stefano Valtolina Italy 13 153 1.2× 36 0.3× 46 0.5× 46 0.6× 6 0.1× 50 570
Erik Nilsen United States 12 55 0.4× 91 0.7× 35 0.4× 27 0.3× 9 0.1× 23 489
Andrea Bunt Canada 18 275 2.1× 114 0.9× 30 0.4× 156 1.9× 24 0.3× 61 1.1k
Dominique L. Scapin France 14 96 0.7× 145 1.1× 19 0.2× 69 0.8× 20 0.3× 36 862
Giuseppe Desolda Italy 13 97 0.7× 36 0.3× 137 1.6× 77 0.9× 9 0.1× 60 686
Munéo Kitajima Japan 13 170 1.3× 63 0.5× 12 0.1× 24 0.3× 42 0.6× 61 620
Marco Manca Italy 11 106 0.8× 57 0.4× 155 1.8× 68 0.8× 5 0.1× 45 554

Countries citing papers authored by Advait Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Advait Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Advait Sarkar

This figure shows the co-authorship network connecting the top 25 collaborators of Advait Sarkar. A scholar is included among the top collaborators of Advait Sarkar 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 Advait Sarkar. Advait Sarkar 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.
Tankelevitch, Lev, Elena L. Glassman, Majeed Kazemitabaar, et al.. (2025). Tools for Thought: Research and Design for Understanding, Protecting, and Augmenting Human Cognition with Generative AI. 1–8. 2 indexed citations
2.
Tankelevitch, Lev, et al.. (2024). The Metacognitive Demands and Opportunities of Generative AI. 1–24. 71 indexed citations breakdown →
3.
Xia, Qing, Advait Sarkar, Duncan P. Brumby, & Anna L. Cox. (2024). The Paradox of Spreadsheet Self-Efficacy: Social Incentives for Informal Knowledge Sharing in End-User Programming. 81–88.
4.
Sarkar, Advait. (2024). AI Should Challenge, Not Obey. Communications of the ACM. 67(10). 18–21. 14 indexed citations
5.
Barke, Shraddha, Benjamin G. Zorn, José Cambronero, et al.. (2024). Solving Data-centric Tasks using Large Language Models. 626–638.
6.
7.
Williams, Jack M., Ian Drosos, Andrew D. Gordon, et al.. (2023). COLDECO: An End User Spreadsheet Inspection Tool for AI-Generated Code. 82–91. 9 indexed citations
8.
Rintel, Sean, et al.. (2022). Meeting (the) Pandemic: Videoconferencing Fatigue and Evolving Tensions of Sociality in Enterprise Video Meetings During COVID-19. Computer Supported Cooperative Work (CSCW). 32(2). 347–383. 21 indexed citations
9.
Ragavan, Sruti Srinivasa, Advait Sarkar, & Andrew D. Gordon. (2021). Spreadsheet Comprehension: Guesswork, Giving Up and Going Back to the Author. 1–21. 7 indexed citations
10.
Borghouts, Judith, et al.. (2020). Elastic sheet-defined functions: Generalising spreadsheet functions to variable-size input arrays. Journal of Functional Programming. 30. 8 indexed citations
11.
Jamnik, Mateja, et al.. (2020). Correspondence-based analogies for choosing problem representations. Apollo (University of Cambridge). 1–5. 2 indexed citations
12.
Williams, Jack M., et al.. (2020). Understanding and Inferring Units in Spreadsheets. 1–9. 6 indexed citations
13.
Kochmar, Ekaterina, et al.. (2019). Comparative judgments are more consistent than binary classification for labelling word complexity. Apollo (University of Cambridge). 208–214. 4 indexed citations
14.
Sarkar, Advait, et al.. (2019). Do We Need Natural Language?. 1–6. 9 indexed citations
15.
Sarkar, Advait. (2016). Constructivist Design for Interactive Machine Learning. 1467–1475. 6 indexed citations
16.
Sarkar, Advait, Cecily Morrison, Jonas F. Dorn, et al.. (2016). Setwise Comparison. 261–271. 16 indexed citations
17.
Sarkar, Advait, Martin Spott, Alan F. Blackwell, & Mateja Jamnik. (2016). Visual discovery and model-driven explanation of time series patterns. Apollo (University of Cambridge). 78–86. 7 indexed citations
18.
Sarkar, Advait. (2015). The impact of syntax colouring on program comprehension.. PPIG. 8. 18 indexed citations
19.
Sarkar, Advait. (2015). Confidence, command, complexity: metamodels for structured interaction with machine intelligence.. PPIG. 3. 8 indexed citations
20.
Sarkar, Advait. (2015). Spreadsheet interfaces for usable machine learning. 35. 283–284. 2 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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