Advait Sarkar

1.5k citations
50 papers · 581 indexed · 2 hit papers · h-index 13
Topics
Spreadsheets and End-User Computing (16 papers)Statistics Education and Methodologies (11 papers)Data Visualization and Analytics (6 papers)

In The Last Decade

Advait Sarkar

46 papers receiving 563 citations

Hit Papers

The Metacognitive Demands and Opportunities of Generative AI20242026202520242025204060

Peers

Advait Sarkar
Comparison fields: 5 of 88
  • Artificial Intelligence 133
  • Social Psychology 128
  • Software 85
  • Computer Science Applications 82
  • Automotive Engineering 73
Replace Toby Jia-Jun Li with:
Toby Jia-Jun Li United States
Rita Francese Italy
Stefano Valtolina Italy
Ana Paula Chaves Brazil
Giuseppe Desolda Italy
Norman G. Vinson Canada
Keith Edwards United States
Peter Johnson United Kingdom
Rajesh Vasa Australia
Matthew Butler Australia
Advait Sarkar relative to Toby Jia-Jun Li United States Toby Jia-Jun Li's profile →
Citations per field
00.5×9.1×
Toby Jia-Jun Li · 1×
Citations per year

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
#WorkIndexed citations
1 2
2
The Metacognitive Demands and Opportunities of Generative AIbreakdown →
71
3 0
4 14
5 0
6 2
7 9
8 21
9 7
10 8
11 2
12 6
13 4
14 9
15 6
16 16
17 7
18
The impact of syntax colouring on program comprehension.
18
19
Confidence, command, complexity: metamodels for structured interaction with machine intelligence.
8
20 2

About Advait Sarkar

Advait Sarkar is a scholar working on Software, Statistics and Probability and Computer Science Applications, having authored 50 papers that have together received 581 indexed citations. Recurring topics across this work include Spreadsheets and End-User Computing (16 papers), Statistics Education and Methodologies (11 papers) and Data Visualization and Analytics (6 papers). The work is most often cited by research in Software (85 citations), Computer Science Applications (82 citations) and Health Informatics (19 citations). Advait Sarkar has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent 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. Their work appears in journals such as Communications of the ACM, Disability and Rehabilitation and Transportation.

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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