Thomas C. M. Lee

9.1k total citations · 2 hit papers
192 papers, 5.5k citations indexed

About

Thomas C. M. Lee is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Thomas C. M. Lee has authored 192 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Statistics and Probability, 37 papers in Artificial Intelligence and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in Thomas C. M. Lee's work include Statistical Methods and Inference (38 papers), Advanced Statistical Methods and Models (30 papers) and Image and Signal Denoising Methods (20 papers). Thomas C. M. Lee is often cited by papers focused on Statistical Methods and Inference (38 papers), Advanced Statistical Methods and Models (30 papers) and Image and Signal Denoising Methods (20 papers). Thomas C. M. Lee collaborates with scholars based in United States, Hong Kong and Canada. Thomas C. M. Lee's co-authors include Helmut Lütkepohl, William E. Griffiths, Eric R. Ziegel, George G. Judge, Peter Hill, Jeffrey M. Lohr, Craig N. Sawchuk, David F. Tolin, Richard A. Levine and Gabriel A. Rodriguez‐Yam and has published in prestigious journals such as Journal of Clinical Investigation, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Thomas C. M. Lee

176 papers receiving 5.0k 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.

Introduction to the Theory and Practice of Econometrics

1989 1.6k citations Thomas C. M. Lee et al. profile →
Journal of Computational and Graphical Statistics

2014 320 citations Thomas C. M. Lee et al. profile →

Peers

Thomas C. M. Lee

SP

EE

AI

MB

OPHTH

B. M. Brown United States

Mia Hubert Belgium

Roy E. Welsch United States

Susan J. Devlin United States

Clark Glymour United States

Andrea Johnson United States

Myles Hollander United States

Edna Schechtman Israel

David Firth United Kingdom

Jun Shao United States

B. M. Brown United States

Thomas C. M. Lee

1.1k ×1.1

SP

343 ×0.4

EE

509 ×0.9

AI

1.4k ×2.6

MB

194 ×0.4

OPHTH

Citations per year, relative to Thomas C. M. Lee Thomas C. M. Lee (= 1×) peers B. M. Brown

Countries citing papers authored by Thomas C. M. Lee

Since Specialization

Citations

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

Fields of papers citing papers by Thomas C. M. Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas C. M. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas C. M. Lee. A scholar is included among the top collaborators of Thomas C. M. 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 Thomas C. M. Lee. Thomas C. M. Lee 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:

20 of 20 papers shown

1.

Sharpnack, James, et al.. (2025). Improving lung cancer diagnosis and survival prediction with deep learning and CT imaging. PLoS ONE. 20(6). e0323174–e0323174. 2 indexed citations

2.

Davis, Richard A., Thomas C. M. Lee, & Gabriel A. Rodriguez‐Yam. (2025). Simultaneous Detection of Structural Breaks and Outliers in Time Series. Journal of Time Series Analysis.

3.

Wang, Jue, V. Kashyap, Thomas C. M. Lee, David A. van Dyk, & A. Zezas. (2025). Auto-BUQ: Uncertainty Quantification for the Boundaries of Segmented Events. The Astronomical Journal. 169(6). 329–329.

4.

Lee, Thomas C. M., et al.. (2024). An integer clustering approach for modeling large-scale EV fleets with guaranteed performance. Electric Power Systems Research. 236. 110650–110650. 2 indexed citations

5.

Li, Yao, et al.. (2024). Adversarial Examples Detection With Bayesian Neural Network. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(5). 3654–3664. 1 indexed citations

6.

Hsieh, Cho‐Jui, et al.. (2023). Fast block-wise partitioning for extreme multi-label classification. Data Mining and Knowledge Discovery. 37(6). 2192–2215. 1 indexed citations

7.

Štingl, Katarína, Krunoslav Stingl, Mark W. Reid, et al.. (2023). Full-field Scotopic Threshold Improvement after Voretigene Neparvovec-rzyl Treatment Correlates with Chorioretinal Atrophy. Ophthalmology. 130(7). 764–770. 29 indexed citations

8.

Fan, Minjie, Jue Wang, V. Kashyap, et al.. (2023). Identifying Diffuse Spatial Structures in High-energy Photon Lists. The Astronomical Journal. 165(2). 66–66. 2 indexed citations

9.

Lee, Thomas C. M., et al.. (2022). High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference. Journal of Computational and Graphical Statistics. 32(1). 226–240.

10.

Lee, Thomas C. M., et al.. (2022). When might we break the rules? A statistical analysis of aesthetics in photographs. PLoS ONE. 17(7). e0269152–e0269152. 1 indexed citations

11.

Lee, Thomas C. M., et al.. (2022). Uncertainty Quantification for Sparse Estimation of Spectral Lines. IEEE Transactions on Signal Processing. 70. 6243–6256. 3 indexed citations

12.

Hannig, Jan, et al.. (2022). Uncertainty Quantification in Graphon Estimation Using Generalized Fiducial Inference. IEEE Transactions on Signal and Information Processing over Networks. 8. 597–609.

13.

Lee, Thomas C. M., et al.. (2022). Statistical Consistency for Change Point Detection and Community Estimation in Time-Evolving Dynamic Networks. IEEE Transactions on Signal and Information Processing over Networks. 8. 215–227. 3 indexed citations

14.

Lee, Thomas C. M., et al.. (2022). Change Point Detection and Node Clustering for Time Series of Graphs. IEEE Transactions on Signal Processing. 70. 3165–3180. 2 indexed citations

15.

Lee, Thomas C. M., et al.. (2021). Generalized Fiducial Inference for Threshold Estimation in Dose–Response and Regression Settings. Journal of Agricultural Biological and Environmental Statistics. 27(1). 109–124.

16.

Hannig, Jan, et al.. (2021). Covariance estimation via fiducial inference. SHILAP Revista de lepidopterología. 5(4). 316–331. 2 indexed citations

17.

Matsuo, Tomoko, Minjie Fan, Xueling Shi, et al.. (2021). Multiresolution Modeling of High‐Latitude Ionospheric Electric Field Variability and Impact on Joule Heating Using SuperDARN Data. Journal of Geophysical Research Space Physics. 126(9). e2021JA029196–e2021JA029196. 5 indexed citations

18.

Hannig, Jan, et al.. (2021). Method G: Uncertainty Quantification for Distributed Data Problems Using Generalized Fiducial Inference. Journal of Computational and Graphical Statistics. 30(4). 934–945. 2 indexed citations

19.

Wong, Raymond K. W., et al.. (2020). Network Estimation via Graphon With Node Features. IEEE Transactions on Network Science and Engineering. 7(3). 2078–2089. 5 indexed citations

20.

Chavala, Sai H., Younghee Kim, Laura Tudisco, et al.. (2013). Retinal angiogenesis suppression through small molecule activation of p53. Journal of Clinical Investigation. 123(10). 4170–4181. 24 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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