Pulkit Agrawal

5.3k total citations · 1 hit paper
46 papers, 1.4k citations indexed

About

Pulkit Agrawal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Pulkit Agrawal has authored 46 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 12 papers in Control and Systems Engineering. Recurrent topics in Pulkit Agrawal's work include Robot Manipulation and Learning (12 papers), Human Pose and Action Recognition (7 papers) and Reinforcement Learning in Robotics (5 papers). Pulkit Agrawal is often cited by papers focused on Robot Manipulation and Learning (12 papers), Human Pose and Action Recognition (7 papers) and Reinforcement Learning in Robotics (5 papers). Pulkit Agrawal collaborates with scholars based in United States, United Kingdom and Taiwan. Pulkit Agrawal's co-authors include Jitendra Malik, João Carreira, Mandar A. Aras, Kirsten E. Fleischmann, Sanjiv J. Shah, Geoffrey H. Tison, Lauren Beussink‐Nelson, Mats Christian Højbjerg Lassen, Ruzena Bajcsy and Eugene Fan and has published in prestigious journals such as Circulation, Journal of Medical Internet Research and International Journal of Production Research.

In The Last Decade

Pulkit Agrawal

39 papers receiving 1.3k citations

Hit Papers

Fully Automated Echocardiogram Interpretation in Clinical... 2018 2026 2020 2023 2018 100 200 300 400 500
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. Fully Automated Echocardiogram Interpretation in Clinical Practice
    2018 568 citations Jeffrey Zhang, Sravani Gajjala et al. Circulation profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pulkit Agrawal United States 14 429 372 326 289 231 46 1.4k
Siti Nurmaini Indonesia 21 261 0.6× 523 1.4× 494 1.5× 123 0.4× 222 1.0× 190 1.7k
Kumaradevan Punithakumar Canada 22 389 0.9× 447 1.2× 255 0.8× 489 1.7× 305 1.3× 130 1.5k
Celia Shahnaz Bangladesh 20 440 1.0× 226 0.6× 429 1.3× 177 0.6× 388 1.7× 153 1.8k
Evangelos B. Mazomenos United Kingdom 18 195 0.5× 148 0.4× 376 1.2× 207 0.7× 375 1.6× 68 1.1k
Anas Tahir Qatar 19 259 0.6× 586 1.6× 267 0.8× 872 3.0× 392 1.7× 32 1.8k
R. James Housden United Kingdom 22 230 0.5× 89 0.2× 213 0.7× 579 2.0× 652 2.8× 76 1.4k
Shivajirao M. Jadhav India 15 240 0.6× 474 1.3× 242 0.7× 388 1.3× 173 0.7× 25 1.2k
Xiang Yu China 17 599 1.4× 570 1.5× 30 0.1× 456 1.6× 169 0.7× 49 1.6k
Friso De Boer Australia 20 174 0.4× 464 1.2× 277 0.8× 359 1.2× 243 1.1× 69 1.5k
Fırat Hardalaç Türkiye 16 152 0.4× 198 0.5× 101 0.3× 229 0.8× 173 0.7× 79 1.1k

Countries citing papers authored by Pulkit Agrawal

Since Specialization
Citations

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

Fields of papers citing papers by Pulkit Agrawal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pulkit Agrawal

This figure shows the co-authorship network connecting the top 25 collaborators of Pulkit Agrawal. A scholar is included among the top collaborators of Pulkit Agrawal 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 Pulkit Agrawal. Pulkit Agrawal 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.
Greenman, Kevin P., et al.. (2025). Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules. npj Computational Materials. 11(1).
2.
Simeonov, Anthony, et al.. (2024). Lifelong Robot Learning with Human Assisted Language Planners. 523–529. 4 indexed citations
3.
Berg, Jacob, et al.. (2024). Rank2Reward: Learning Shaped Reward Functions from Passive Video. 2806–2813.
4.
5.
Simeonov, Anthony, et al.. (2024). JUICER: Data-Efficient Imitation Learning for Robotic Assembly. 5096–5103. 4 indexed citations
6.
Agrawal, Pulkit, et al.. (2024). Learning Force Control for Legged Manipulation. 15366–15372. 9 indexed citations
7.
Hong, Zhang-Wei, et al.. (2024). Maximizing Quadruped Velocity by Minimizing Energy. 11467–11473. 2 indexed citations
8.
9.
Wang, Yanwei, et al.. (2023). Visual Pre-Training for Navigation: What Can We Learn from Noise?. 34. 3897–3902. 2 indexed citations
10.
11.
Simeonov, Anthony, Yilun Du, Andrea Tagliasacchi, et al.. (2022). Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. 2022 International Conference on Robotics and Automation (ICRA). 6394–6400. 95 indexed citations
12.
Bayen, É., et al.. (2021). Reduction of Time on the Ground Related to Real-Time Video Detection of Falls in Memory Care Facilities: Observational Study. Journal of Medical Internet Research. 23(6). e17551–e17551. 7 indexed citations
13.
Collins, Jasmine, et al.. (2020). Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments.. Cognitive Science. 1 indexed citations
14.
Cheung, Brian, Alexander V. Terekhov, Yubei Chen, Pulkit Agrawal, & Bruno A. Olshausen. (2019). Superposition of many models into one. arXiv (Cornell University). 32. 10867–10876. 16 indexed citations
15.
Zhang, Jeffrey, Sravani Gajjala, Pulkit Agrawal, et al.. (2018). Fully Automated Echocardiogram Interpretation in Clinical Practice. Circulation. 138(16). 1623–1635. 568 indexed citations breakdown →
16.
Dubey, Rachit, et al.. (2018). Investigating Human Priors for Playing Video Games. International Conference on Machine Learning. 1348–1356. 5 indexed citations
17.
Fragkiadaki, Katerina, Pulkit Agrawal, Sergey Levine, & Jitendra Malik. (2016). Learning Visual Predictive Models of Physics for Playing Billiards. International Conference on Learning Representations. 28 indexed citations
18.
Denil, Misha, Pulkit Agrawal, Tejas D. Kulkarni, et al.. (2016). Learning to Perform Physics Experiments via Deep Reinforcement Learning.. International Conference on Learning Representations. 2 indexed citations
19.
Agrawal, Pulkit, Ashvin Nair, Pieter Abbeel, Jitendra Malik, & Sergey Levine. (2016). Learning to poke by poking: experiential learning of intuitive physics. Neural Information Processing Systems. 29. 5092–5100. 128 indexed citations
20.
Gweon, Gahgene, et al.. (2011). The automatic assessment of knowledge integration processes in project teams.. Computer Supported Collaborative Learning. 7 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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