Kaylee Burns

636 total citations
6 papers, 53 citations indexed

About

Kaylee Burns is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kaylee Burns has authored 6 papers receiving a total of 53 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Control and Systems Engineering and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kaylee Burns's work include Multimodal Machine Learning Applications (2 papers), Robot Manipulation and Learning (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Kaylee Burns is often cited by papers focused on Multimodal Machine Learning Applications (2 papers), Robot Manipulation and Learning (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Kaylee Burns collaborates with scholars based in United States and United Kingdom. Kaylee Burns's co-authors include Erin Grant, Alison Gopnik, Thomas L. Griffiths, Aida Nematzadeh, Ken Goldberg, Pete Florence, Dorsa Sadigh, Tony Z. Zhao, Stefan Schaal and Emma Brunskill and has published in prestigious journals such as 2022 International Conference on Robotics and Automation (ICRA).

In The Last Decade

Kaylee Burns

4 papers receiving 48 citations

Peers

Kaylee Burns

AI

CVPR

SP

DEP

CN

Cédric Colas France

Rachel Bawden France

Sushma A. Akoju United States

Rudolf Kadlec Czechia

Aina Garí Soler France

Sung-Lin Yeh United Kingdom

Fereshte Khani United States

Jaap Jumelet Netherlands

Joshua Rule United States

Alex Tamkin United States

Cédric Colas France

Kaylee Burns

27 ×0.7

AI

4 ×0.3

CVPR

9 ×0.9

SP

8 ×0.9

DEP

13 ×1.9

CN

Citations per year, relative to Kaylee Burns Kaylee Burns (= 1×) peers Cédric Colas

Countries citing papers authored by Kaylee Burns

Since Specialization

Citations

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

Fields of papers citing papers by Kaylee Burns

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaylee Burns

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

All Works

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6 of 6 papers shown

1.

Mirchandani, Suvir, et al.. (2025). RoboCrowd: Scaling Robot Data Collection Through Crowdsourcing. 1392–1399.

2.

Burns, Kaylee, et al.. (2024). A Fast and Accurate Machine Learning Autograder for the Breakout Assignment. 736–742.

3.

Burns, Kaylee, et al.. (2024). GenCHiP: Generating Robot Policy Code for High-Precision and Contact-Rich Manipulation Tasks. 9596–9603. 1 indexed citations

4.

Florence, Pete, et al.. (2022). Implicit Kinematic Policies: Unifying Joint and Cartesian Action Spaces in End-to-End Robot Learning. 2022 International Conference on Robotics and Automation (ICRA). 2656–2662. 8 indexed citations

5.

Nematzadeh, Aida, Kaylee Burns, Erin Grant, Alison Gopnik, & Thomas L. Griffiths. (2018). Evaluating Theory of Mind in Question Answering. 2392–2400. 39 indexed citations

6.

Burns, Kaylee, Aida Nematzadeh, Erin Grant, Alison Gopnik, & Thomas L. Griffiths. (2018). Exploiting Attention to Reveal Shortcomings in Memory Models. 378–380. 5 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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