Seok‐Bum Ko

4.2k citations
222 papers · 2.8k · h-index 26

Impact in

Papers in

Seok‐Bum Ko

209 papers receiving 2.6k citations

Peers

Seok‐Bum Ko
Comparison fields: 5 of 129
  • Hardware and Architecture 397
  • Computational Theory and Mathematics 565
  • Signal Processing 310
  • Computer Vision and Pattern Recognition 539
  • Health Informatics 26
Replace Pramod Kumar Meher with:
Pramod Kumar Meher Singapore
Xuan Zeng China
Khan A. Wahid Canada
Dian Zhou China
Miriam Leeser United States
W.K. Jenkins United States
Gerd Ascheid Germany
Jayaraman J. Thiagarajan United States
Yik‐Chung Wu Hong Kong
Animashree Anandkumar United States
Seok‐Bum Ko relative to Pramod Kumar Meher Singapore Pramod Kumar Meher's profile →
Citations per field
00.5×5.2×
Pramod Kumar Meher · 1×
Citations per year

Countries citing papers authored by Seok‐Bum Ko

Since Specialization
Citations

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

Fields of papers citing papers by Seok‐Bum Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seok‐Bum Ko. 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 Seok‐Bum Ko. The network helps show where Seok‐Bum Ko may publish in the future.

Co-authors

The 25 scholars most cited alongside Seok‐Bum Ko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Seok‐Bum Ko Line = papers co-authored together Seok‐Bum Ko links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 222 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017275
2 2020135
3 202297
4 201295
5 201988
6 201765
7 200858
8 201951
9 202049
10 201048
11 201546
12 202045
13 202043
14 201942
15 202038
16 202036
17 201135
18 201934
19 201231
20 202030

About Seok‐Bum Ko

Seok‐Bum Ko is a scholar working on Electrical and Electronic Engineering, Computational Theory and Mathematics, Hardware and Architecture, Computer Vision and Pattern Recognition and Signal Processing, having authored 222 papers that have together received 2.8k indexed citations. Recurring topics across this work include Low-power high-performance VLSI design (52 papers), Numerical Methods and Algorithms (46 papers), Digital Filter Design and Implementation (34 papers), Advanced Memory and Neural Computing (25 papers), Parallel Computing and Optimization Techniques (23 papers), Interconnection Networks and Systems (23 papers), Analog and Mixed-Signal Circuit Design (16 papers) and Embedded Systems Design Techniques (13 papers). The work is most often cited by research in Hardware and Architecture (397 citations), Computational Theory and Mathematics (565 citations), Signal Processing (310 citations), Computer Vision and Pattern Recognition (539 citations) and Health Informatics (26 citations). Seok‐Bum Ko has collaborated with scholars based in Canada, India and South Korea. Frequent co-authors include Younhee Choi, Hao Zhang, Khan A. Wahid, Hyuk-Jae Lee, Gong Yong Jin, Dongdong Chen, Qiao Zhang, S. Venkatachalam, Hao Zhang and Yi Wang. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Multimedia Tools and Applications, IEEE Transactions on Circuits & Systems II Express Briefs and IET Intelligent Transport Systems.

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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