Aakriti Kumar

527 total citations · 1 hit paper
10 papers, 152 citations indexed

About

Aakriti Kumar is a scholar working on Artificial Intelligence, Safety Research and Health Informatics. According to data from OpenAlex, Aakriti Kumar has authored 10 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Safety Research and 2 papers in Health Informatics. Recurrent topics in Aakriti Kumar's work include Explainable Artificial Intelligence (XAI) (6 papers), Ethics and Social Impacts of AI (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Aakriti Kumar is often cited by papers focused on Explainable Artificial Intelligence (XAI) (6 papers), Ethics and Social Impacts of AI (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Aakriti Kumar collaborates with scholars based in United States, Netherlands and Australia. Aakriti Kumar's co-authors include Mark Steyvers, Padhraic Smyth, Heliodoro Tejeda, Jeffrey N. Rouder, Julia M. Haaf, Aaron S. Benjamin, Andrew Heathcote, Kumar Akash, Jessica Hullman and Teruhisa Misu and has published in prestigious journals such as Psychological Review, Perspectives on Psychological Science and Psychonomic Bulletin & Review.

In The Last Decade

Aakriti Kumar

9 papers receiving 146 citations

Hit Papers

align trajectories

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.

What large language models know and what people think they know

2025 29 citations Mark Steyvers, Heliodoro Tejeda et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aakriti Kumar United States	5	69	30	26	24	22	10	152
Iris Heung Yue Yim United Kingdom	8	61 0.9×	28 0.9×	40 1.5×	11 0.5×	14 0.6×	10	235
Carina Prunkl United Kingdom	7	37 0.5×	50 1.7×	32 1.2×	24 1.0×	11 0.5×	11	123
Isabel O. Gallegos United States	3	79 1.1×	17 0.6×	21 0.8×	5 0.2×	5 0.2×	6	156
Hyangeun Ji United States	4	101 1.5×	7 0.2×	36 1.4×	8 0.3×	24 1.1×	7	249
Paul Röttger United Kingdom	8	132 1.9×	28 0.9×	12 0.5×	10 0.4×	19 0.9×	26	189
Muhammad Ali Chaudhry United Kingdom	3	60 0.9×	16 0.5×	37 1.4×	3 0.1×	4 0.2×	6	176
I Wayan Numertayasa Indonesia	4	56 0.8×	25 0.8×	69 2.7×	4 0.2×	7 0.3×	28	207
Darwin Darwin Indonesia	3	114 1.7×	17 0.6×	83 3.2×	5 0.2×	10 0.5×	8	308
Inda Indrawati Indonesia	4	90 1.3×	12 0.4×	72 2.8×	4 0.2×	7 0.3×	9	237
Diyenti Rusdin Indonesia	4	122 1.8×	17 0.6×	90 3.5×	4 0.2×	10 0.5×	9	327

Countries citing papers authored by Aakriti Kumar

Since Specialization

Citations

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

Fields of papers citing papers by Aakriti Kumar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aakriti Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Aakriti Kumar. A scholar is included among the top collaborators of Aakriti Kumar 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 Aakriti Kumar. Aakriti Kumar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Kumar, Aakriti, et al.. (2025). Characterizing Photorealism and Artifacts in Diffusion Model-Generated Images. 1–26. 1 indexed citations

2.

Steyvers, Mark, et al.. (2025). What large language models know and what people think they know. Nature Machine Intelligence. 7(2). 221–231. 29 indexed citations breakdown →

3.

Rouder, Jeffrey N., Aakriti Kumar, & Julia M. Haaf. (2023). Why many studies of individual differences with inhibition tasks may not localize correlations. Psychonomic Bulletin & Review. 30(6). 2049–2066. 24 indexed citations

4.

Kumar, Aakriti, Padhraic Smyth, & Mark Steyvers. (2023). Differentiating mental models of self and others: A hierarchical framework for knowledge assessment.. Psychological Review. 130(6). 1566–1591. 2 indexed citations

5.

Kumar, Aakriti, et al.. (2023). Capturing Humans’ Mental Models of AI: An Item Response Theory Approach. arXiv (Cornell University). 1723–1734. 10 indexed citations

6.

Kumar, Aakriti, et al.. (2023). When Do Drivers Intervene In Autonomous Driving?. 301–305.

7.

Steyvers, Mark & Aakriti Kumar. (2023). Three Challenges for AI-Assisted Decision-Making. Perspectives on Psychological Science. 19(5). 722–734. 55 indexed citations

8.

Kumar, Aakriti, Aaron S. Benjamin, Andrew Heathcote, & Mark Steyvers. (2022). Comparing models of learning and relearning in large-scale cognitive training data sets. npj Science of Learning. 7(1). 24–24. 4 indexed citations

9.

Tejeda, Heliodoro, Aakriti Kumar, Padhraic Smyth, & Mark Steyvers. (2022). AI-Assisted Decision-making: a Cognitive Modeling Approach to Infer Latent Reliance Strategies. Computational Brain & Behavior. 5(4). 491–508. 24 indexed citations

10.

Kumar, Aakriti, et al.. (2021). Explaining Algorithm Aversion with Metacognitive Bandits. eScholarship (California Digital Library). 43(43). 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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