Jee Choi

1.1k total citations · 1 hit paper
25 papers, 762 citations indexed

About

Jee Choi is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computational Mathematics. According to data from OpenAlex, Jee Choi has authored 25 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Hardware and Architecture, 12 papers in Computer Networks and Communications and 7 papers in Computational Mathematics. Recurrent topics in Jee Choi's work include Parallel Computing and Optimization Techniques (16 papers), Tensor decomposition and applications (7 papers) and Advanced Data Storage Technologies (6 papers). Jee Choi is often cited by papers focused on Parallel Computing and Optimization Techniques (16 papers), Tensor decomposition and applications (7 papers) and Advanced Data Storage Technologies (6 papers). Jee Choi collaborates with scholars based in United States, India and Germany. Jee Choi's co-authors include Richard Vuduc, Amik Singh, Robert J. Fowler, Aparna Chandramowlishwaran, Xing Liu, Marat Dukhan, Xing Liu, Venkatesan T. Chakaravarthy, Jiajia Li and Ioakeim Perros and has published in prestigious journals such as IEEE Transactions on Parallel and Distributed Systems, ACM SIGPLAN Notices and Journal of Signal Processing Systems.

In The Last Decade

Jee Choi

23 papers receiving 731 citations

Hit Papers

Model-driven autotuning of sparse matrix-vector multiply ... 2010 2026 2015 2020 2010 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-driven autotuning of sparse matrix-vector multiply on GPUs
    2010 279 citations Jee Choi, Amik Singh et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jee Choi United States 10 589 456 133 131 106 25 762
Field G. Zee United States 12 506 0.9× 371 0.8× 157 1.2× 146 1.1× 38 0.4× 21 662
Muthu Manikandan Baskaran United States 14 633 1.1× 504 1.1× 185 1.4× 71 0.5× 165 1.6× 41 831
Jiajia Li United States 19 624 1.1× 371 0.8× 294 2.2× 85 0.6× 271 2.6× 49 948
Paolo Bientinesi Germany 13 344 0.6× 289 0.6× 119 0.9× 180 1.4× 35 0.3× 56 652
Brian Vinter Denmark 10 472 0.8× 433 0.9× 138 1.0× 103 0.8× 33 0.3× 54 666
Ernie Chan United States 12 435 0.7× 401 0.9× 125 0.9× 121 0.9× 19 0.2× 15 609
Albert Hartono United States 8 778 1.3× 579 1.3× 171 1.3× 81 0.6× 31 0.3× 9 894
Emmanuel Agullo France 14 481 0.8× 403 0.9× 88 0.7× 191 1.5× 25 0.2× 34 727
Amik Singh United States 6 409 0.7× 348 0.8× 88 0.7× 129 1.0× 19 0.2× 6 507
Rajib Nath United States 8 329 0.6× 241 0.5× 50 0.4× 141 1.1× 26 0.2× 11 473

Countries citing papers authored by Jee Choi

Since Specialization
Citations

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

Fields of papers citing papers by Jee Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jee Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Jee Choi. A scholar is included among the top collaborators of Jee Choi 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 Jee Choi. Jee Choi 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.
Checconi, Fabio, et al.. (2025). Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation. IEEE Transactions on Parallel and Distributed Systems. 36(5). 1025–1041.
2.
3.
McLaughlin, Joseph K., Jee Choi, & Ramakrishnan Durairajan. (2023). ×Grid: A Location-oriented Topology Design for LEO Satellites. 37–42. 2 indexed citations
4.
Choi, Jee, Xing Liu, & Venkatesan T. Chakaravarthy. (2018). High-performance dense tucker decomposition on GPU clusters. IEEE International Conference on High Performance Computing, Data, and Analytics. 543–553. 6 indexed citations
5.
Choi, Jee, Xing Liu, & Venkatesan T. Chakaravarthy. (2018). High-Performance Dense Tucker Decomposition on GPU Clusters. 543–553. 13 indexed citations
6.
Choi, Jee, et al.. (2018). Blocking Optimization Techniques for Sparse Tensor Computation. Maryland Shared Open Access Repository (USMAI Consortium). 568–577. 18 indexed citations
7.
Li, Jiajia, Jee Choi, Ioakeim Perros, Jimeng Sun, & Richard Vuduc. (2017). Model-Driven Sparse CP Decomposition for Higher-Order Tensors. 1048–1057. 33 indexed citations
8.
Chakaravarthy, Venkatesan T., et al.. (2017). On Optimizing Distributed Tucker Decomposition for Dense Tensors. 1038–1047. 21 indexed citations
9.
Checconi, Fabio, et al.. (2017). Data Analytics with NVLink. 89–96. 4 indexed citations
10.
Choi, Jee & Richard Vuduc. (2016). Analyzing the Energy Efficiency of the Fast Multipole Method Using a DVFS-Aware Energy Model. 79–88. 5 indexed citations
11.
Liu, Xing, Fabio Checconi, Jee Choi, et al.. (2016). An Early Performance Study of Large-Scale POWER8 SMP Systems. 59. 263–272. 3 indexed citations
12.
Choi, Jee, Aparna Chandramowlishwaran, Kamesh Madduri, & Richard Vuduc. (2014). A CPU. 46. 64–71. 9 indexed citations
13.
Choi, Jee, Aparna Chandramowlishwaran, Kamesh Madduri, & Richard Vuduc. (2014). A CPU. 46. 64–71. 6 indexed citations
14.
Choi, Jee, Marat Dukhan, Xing Liu, & Richard Vuduc. (2014). Algorithmic Time, Energy, and Power on Candidate HPC Compute Building Blocks. 447–457. 50 indexed citations
15.
Choi, Jee & Richard Vuduc. (2013). How much (execution) time and energy does my algorithm cost?. XRDS Crossroads The ACM Magazine for Students. 19(3). 49–51. 5 indexed citations
16.
Choi, Jee & Richard Vuduc. (2012). Modeling and Analysis for Performance and Power. 62. 2466–2469. 2 indexed citations
17.
Vuduc, Richard, et al.. (2010). On the limits of GPU acceleration. 13–13. 80 indexed citations
18.
Choi, Jee, Amik Singh, & Richard Vuduc. (2010). Model-driven autotuning of sparse matrix-vector multiply on GPUs. 115–126. 279 indexed citations breakdown →
19.
Choi, Jee, Amik Singh, & Richard Vuduc. (2010). Model-driven autotuning of sparse matrix-vector multiply on GPUs. ACM SIGPLAN Notices. 45(5). 115–126. 114 indexed citations
20.

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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