Kookjin Lee

1.2k total citations · 1 hit paper
26 papers, 462 citations indexed

About

Kookjin Lee is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kookjin Lee has authored 26 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Statistical and Nonlinear Physics, 10 papers in Artificial Intelligence and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kookjin Lee's work include Model Reduction and Neural Networks (13 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Probabilistic and Robust Engineering Design (5 papers). Kookjin Lee is often cited by papers focused on Model Reduction and Neural Networks (13 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Probabilistic and Robust Engineering Design (5 papers). Kookjin Lee collaborates with scholars based in United States, South Korea and India. Kookjin Lee's co-authors include Noseong Park, Eric Parish, Dong‐Eun Lee, Jung-Eun Kim, Jaideep Ray, Kevin Carlberg, Dan Keun Sung, Heonshik Shin, Yongwoo Cho and Jaesheung Shin and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Kookjin Lee

23 papers receiving 443 citations

Hit Papers

Model reduction for nonlinear dynamical systems using dee... 2023 2026 2024 2025 2023 50 100 150 200 250
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. Model reduction for nonlinear dynamical systems using deep convolutional autoencoders.
    2023 251 citations Kookjin Lee OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kookjin Lee United States 9 302 161 88 72 60 26 462
Elizabeth Qian United States 7 215 0.7× 108 0.7× 98 1.1× 42 0.6× 96 1.6× 10 378
Yiping Lu China 5 260 0.9× 93 0.6× 67 0.8× 101 1.4× 38 0.6× 17 386
Roberto Molinaro Switzerland 9 347 1.1× 177 1.1× 47 0.5× 103 1.4× 66 1.1× 10 539
Alessandro Alla Italy 9 331 1.1× 156 1.0× 107 1.2× 57 0.8× 39 0.7× 27 469
Suraj Pawar United States 13 287 1.0× 246 1.5× 52 0.6× 66 0.9× 106 1.8× 34 556
Jens Berg Sweden 9 419 1.4× 279 1.7× 84 1.0× 95 1.3× 57 0.9× 11 656
Deep Ray United States 11 448 1.5× 370 2.3× 122 1.4× 99 1.4× 110 1.8× 24 727
Matthew O. Williams United States 12 446 1.5× 202 1.3× 130 1.5× 46 0.6× 76 1.3× 27 596
Tong Qin United States 7 203 0.7× 165 1.0× 82 0.9× 68 0.9× 29 0.5× 11 387

Countries citing papers authored by Kookjin Lee

Since Specialization
Citations

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

Fields of papers citing papers by Kookjin Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kookjin Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Kookjin Lee. A scholar is included among the top collaborators of Kookjin Lee 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 Kookjin Lee. Kookjin Lee 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.
Lee, Kookjin, et al.. (2025). FastLRNR and Sparse Physics Informed Backpropagation. Results in Applied Mathematics. 25. 100547–100547. 1 indexed citations
2.
Trask, Nathaniel, Carianne Martinez, Kookjin Lee, et al.. (2024). Unsupervised physics-informed disentanglement of multimodal materials data. Materials Today. 80. 286–296. 5 indexed citations
3.
Rim, Donsub, et al.. (2024). A Stability Analysis of Neural Networks and Its Application to Tsunami Early Warning. SHILAP Revista de lepidopterología. 1(4). 1 indexed citations
4.
5.
Cho, Woojin, Kookjin Lee, Sanghyun Hong, et al.. (2024). Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11543–11551. 2 indexed citations
6.
Trask, Nathaniel, Carianne Martinez, Kookjin Lee, et al.. (2024). Unsupervised physics-informed disentanglement of multimodal data. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 7(1). 418–445. 3 indexed citations
7.
Choi, Jeongwhan, et al.. (2023). Climate modeling with neural advection–diffusion equation. Knowledge and Information Systems. 65(6). 2403–2427. 8 indexed citations
8.
Lee, Kookjin. (2023). Model reduction for nonlinear dynamical systems using deep convolutional autoencoders.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 251 indexed citations breakdown →
9.
Lee, Dong‐Eun, et al.. (2022). Deep Sequence Models for Packet Stream Analysis and Early Decisions. 56–63. 1 indexed citations
10.
Lee, Kookjin, Howard C. Elman, Catherine E. Powell, & Dong‐Eun Lee. (2022). Enhanced alternating energy minimization methods for stochastic galerkin matrix equations. BIT Numerical Mathematics. 62(3). 965–994.
11.
Lee, Dong‐Eun, et al.. (2021). A Novel Method to Solve Neural Knapsack Problems. International Conference on Machine Learning. 6414–6424. 1 indexed citations
12.
Lee, Kookjin, et al.. (2021). Projection-based model reduction of dynamical systems using space-time subspace and machine learning. arXiv (Cornell University). 10 indexed citations
13.
Lee, Kookjin, Jaideep Ray, & Cosmin Safta. (2021). The predictive skill of convolutional neural networks models for disease forecasting. PLoS ONE. 16(7). e0254319–e0254319. 8 indexed citations
14.
Lee, Kookjin & Kevin Carlberg. (2021). Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws [Poster]. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations
15.
Kim, Jung-Eun, et al.. (2021). DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation. Proceedings of the AAAI Conference on Artificial Intelligence. 35(9). 8146–8154. 59 indexed citations
16.
Lee, Kookjin & Eric Parish. (2021). Parameterized neural ordinary differential equations: applications to computational physics problems. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 477(2253). 20210162–20210162. 32 indexed citations
17.
Lee, Kookjin, Howard C. Elman, & Bedřich Sousedík. (2019). A Low-Rank Solver for the Navier--Stokes Equations with Uncertain Viscosity. SIAM/ASA Journal on Uncertainty Quantification. 7(4). 1275–1300. 6 indexed citations
18.
Lee, Kookjin & Bedřich Sousedík. (2018). Inexact Methods for Symmetric Stochastic Eigenvalue Problems. SIAM/ASA Journal on Uncertainty Quantification. 6(4). 1744–1776. 2 indexed citations
19.
Park, Noseong, Ankesh Anand, Kookjin Lee, et al.. (2017). MMGAN: Manifold Matching Generative Adversarial Network for Generating Images.. arXiv (Cornell University). 2 indexed citations
20.
Lee, Kookjin, Jaesheung Shin, Yongwoo Cho, et al.. (2012). A group-based communication scheme based on the location information of MTC devices in cellular networks. 4899–4903. 23 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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