Seung-Jai Min

1.4k total citations · 1 hit paper
23 papers, 684 citations indexed

About

Seung-Jai Min is a scholar working on Computer Networks and Communications, Hardware and Architecture and Computer Vision and Pattern Recognition. According to data from OpenAlex, Seung-Jai Min has authored 23 papers receiving a total of 684 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Networks and Communications, 10 papers in Hardware and Architecture and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Seung-Jai Min's work include Parallel Computing and Optimization Techniques (10 papers), Distributed and Parallel Computing Systems (6 papers) and Advanced Data Storage Technologies (3 papers). Seung-Jai Min is often cited by papers focused on Parallel Computing and Optimization Techniques (10 papers), Distributed and Parallel Computing Systems (6 papers) and Advanced Data Storage Technologies (3 papers). Seung-Jai Min collaborates with scholars based in South Korea and United States. Seung-Jai Min's co-authors include Rudolf Eigenmann, Seyong Lee, Katherine Yelick, Costin Iancu, Samuel P. Midkiff, Hansang Bae, Ayon Basumallik, Youngjune Gwon, Soo‐Ik Chae and Jongwon Choi and has published in prestigious journals such as Computer, ACM SIGPLAN Notices and IEEE Transactions on Consumer Electronics.

In The Last Decade

Seung-Jai Min

23 papers receiving 646 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.

OpenMP to GPGPU

2009 281 citations Seyong Lee, Seung-Jai Min et al. Purdue e-Pubs (Purdue University System) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seung-Jai Min South Korea	10	504	496	174	106	84	23	684
Vignesh T. Ravi United States	14	437 0.9×	471 0.9×	328 1.9×	66 0.6×	60 0.7×	28	621
Marco Vanneschi Italy	13	424 0.8×	680 1.4×	223 1.3×	120 1.1×	42 0.5×	82	790
Hyojin Sung United States	10	661 1.3×	630 1.3×	175 1.0×	163 1.5×	40 0.5×	32	787
Albert D. Alexandrov United States	7	461 0.9×	559 1.1×	133 0.8×	70 0.7×	45 0.5×	7	660
Michel Steuwer United Kingdom	14	560 1.1×	406 0.8×	128 0.7×	160 1.5×	67 0.8×	51	655
Rashid Kaleem United States	8	365 0.7×	352 0.7×	167 1.0×	114 1.1×	207 2.5×	8	552
Arturo González-Escribano Spain	10	268 0.5×	279 0.6×	101 0.6×	45 0.4×	74 0.9×	60	417
Isaac Gelado Spain	14	710 1.4×	684 1.4×	229 1.3×	70 0.7×	80 1.0×	27	852
Allan Kielstra Canada	5	956 1.9×	961 1.9×	309 1.8×	175 1.7×	63 0.8×	6	1.1k
Diego R. Llanos Spain	12	297 0.6×	313 0.6×	99 0.6×	54 0.5×	71 0.8×	70	472

Countries citing papers authored by Seung-Jai Min

Since Specialization

Citations

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

Fields of papers citing papers by Seung-Jai Min

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seung-Jai Min. 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 Seung-Jai Min. The network helps show where Seung-Jai Min may publish in the future.

Co-authorship network of co-authors of Seung-Jai Min

This figure shows the co-authorship network connecting the top 25 collaborators of Seung-Jai Min. A scholar is included among the top collaborators of Seung-Jai Min 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 Seung-Jai Min. Seung-Jai Min 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.

Jeong, Yonghyun, et al.. (2022). BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2878–2887. 32 indexed citations

2.

Lee, Hyunjae, et al.. (2021). KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding. 5551–5557. 7 indexed citations

3.

Gwon, Youngjune, et al.. (2020). POMO: Policy Optimization with Multiple Optima for Reinforcement Learning. Neural Information Processing Systems. 33. 21188–21198. 1 indexed citations

4.

Choi, Jongwon, et al.. (2020). Visual Domain Adaptation by Consensus-Based Transfer to Intermediate Domain. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 10655–10662. 5 indexed citations

5.

Lee, Hyojung, et al.. (2018). Economic Analysis of Blockchain Technology on Digital Platform Market. 94–103. 7 indexed citations

6.

Min, Seung-Jai, Costin Iancu, & Katherine Yelick. (2011). Hierarchical Work Stealing on Manycore Clusters. 53 indexed citations

7.

Shan, Hongzhang, Filip Blagojević, Seung-Jai Min, et al.. (2010). A Programming Model Performance Study Using the NAS Parallel Benchmarks. Scientific Programming. 18(3-4). 153–167. 18 indexed citations

8.

Bae, Hansang, et al.. (2009). Cetus: A Source-to-Source Compiler Infrastructure for Multicores. Computer. 42(12). 36–42. 98 indexed citations

9.

Lee, Seyong, Seung-Jai Min, & Rudolf Eigenmann. (2009). OpenMP to GPGPU. ACM SIGPLAN Notices. 44(4). 101–110. 74 indexed citations

10.

Lee, Seyong, Seung-Jai Min, & Rudolf Eigenmann. (2009). OpenMP to GPGPU. Purdue e-Pubs (Purdue University System). 101–110. 281 indexed citations breakdown →

11.

Min, Seung-Jai & Rudolf Eigenmann. (2008). Optimizing irregular shared-memory applications for clusters. Purdue e-Pubs (Purdue University System). 256–265. 12 indexed citations

12.

Basumallik, Ayon, Seung-Jai Min, & Rudolf Eigenmann. (2007). Programming Distributed Memory Sytems Using OpenMP. Purdue e-Pubs (Purdue University System). 1–8. 26 indexed citations

13.

Min, Seung-Jai, et al.. (2005). A computationally efficient IDCT algorithm. 2. 973–976. 1 indexed citations

14.

Min, Seung-Jai & Rudolf Eigenmann. (2004). Combined compile-time and runtime-driven, pro-active data movement in software DSM systems. 1–6. 4 indexed citations

15.

Min, Seung-Jai, Ayon Basumallik, & Rudolf Eigenmann. (2003). Optimizing OpenMP Programs on Software Distributed Shared Memory Systems. International Journal of Parallel Programming. 31(3). 225–249. 17 indexed citations

16.

Min, Seung-Jai, et al.. (2002). A study on the stochastic computation using the ratio of one pulses and zero pulses. 6. 471–474. 15 indexed citations

17.

Kim, Han‐Soo, et al.. (2002). Multi-thread VLIW processor architecture for HDTV decoding. 559–562. 4 indexed citations

18.

Park, Sung‐Jun, Seung-Jai Min, & Soo‐Ik Chae. (2002). Stereo correspondence with discrete-time cellular neural networks. 6. 225–228. 3 indexed citations

19.

Min, Seung-Jai, et al.. (1999). A single-chip HDTV A/V decoder for low cost DTV receiver. IEEE Transactions on Consumer Electronics. 45(3). 887–893. 5 indexed citations

20.

Min, Seung-Jai & Soo‐Ik Chae. (1994). Neural network implementation using new pulse arithmetic. International Journal of Electronics. 77(6). 1015–1024. 3 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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