Se-Hyun Yang

1.4k total citations · 1 hit paper
18 papers, 1.0k citations indexed

About

Se-Hyun Yang is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Se-Hyun Yang has authored 18 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Hardware and Architecture, 13 papers in Electrical and Electronic Engineering and 7 papers in Computer Networks and Communications. Recurrent topics in Se-Hyun Yang's work include Parallel Computing and Optimization Techniques (13 papers), Low-power high-performance VLSI design (12 papers) and Advanced Memory and Neural Computing (6 papers). Se-Hyun Yang is often cited by papers focused on Parallel Computing and Optimization Techniques (13 papers), Low-power high-performance VLSI design (12 papers) and Advanced Memory and Neural Computing (6 papers). Se-Hyun Yang collaborates with scholars based in United States, South Korea and Canada. Se-Hyun Yang's co-authors include Babak Falsafi, Michael D. Powell, T. N. Vijaykumar, Kaushik Roy, Kaushik Roy, T.N. Vijaykumar, Andreas Moshovos, Nandita Vijaykumar, Lee Seogjun and Jeongnam Youn and has published in prestigious journals such as IEEE Communications Magazine, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.

In The Last Decade

Se-Hyun Yang

18 papers receiving 946 citations

Hit Papers

Gated-Vdd 2000 2026 2008 2017 2000 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Se-Hyun Yang United States 8 803 682 520 45 27 18 1.0k
Nak Hee Seong United States 9 554 0.7× 451 0.7× 547 1.1× 45 1.0× 8 0.3× 10 730
Jeff Rupley United States 8 414 0.5× 416 0.6× 399 0.8× 45 1.0× 11 0.4× 10 650
V. Srinivasan United States 8 385 0.5× 385 0.6× 252 0.5× 38 0.8× 16 0.6× 14 572
Stefan Rusu United States 15 539 0.7× 808 1.2× 272 0.5× 18 0.4× 78 2.9× 41 959
Varghese George United States 11 513 0.6× 550 0.8× 411 0.8× 22 0.5× 80 3.0× 13 814
Dong Hyuk Woo United States 12 772 1.0× 514 0.8× 769 1.5× 101 2.2× 6 0.2× 23 1.0k
Érika Cota Brazil 19 774 1.0× 619 0.9× 766 1.5× 13 0.3× 24 0.9× 58 956
J. Adam Butts United States 5 348 0.4× 292 0.4× 183 0.4× 39 0.9× 11 0.4× 10 452
J. DeVale United States 5 282 0.4× 377 0.6× 362 0.7× 91 2.0× 11 0.4× 8 626
Ilya Ganusov United States 10 346 0.4× 252 0.4× 266 0.5× 13 0.3× 13 0.5× 14 476

Countries citing papers authored by Se-Hyun Yang

Since Specialization
Citations

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

Fields of papers citing papers by Se-Hyun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Se-Hyun Yang. 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 Se-Hyun Yang. The network helps show where Se-Hyun Yang may publish in the future.

Co-authorship network of co-authors of Se-Hyun Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Se-Hyun Yang. A scholar is included among the top collaborators of Se-Hyun Yang 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 Se-Hyun Yang. Se-Hyun Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Yang, Se-Hyun, et al.. (2013). A 1.6 GHz quad-core application processor manufactured in 32 nm high-k metal gate process for smart mobile devices. IEEE Communications Magazine. 51(4). 94–98. 6 indexed citations
2.
Yang, Se-Hyun, Lee Seogjun, Jae‐Young Lee, et al.. (2012). A 32nm high-k metal gate application processor with GHz multi-core CPU. 214–216. 13 indexed citations
3.
Yang, Se-Hyun, et al.. (2011). Performance Evaluation of Wireless Sensor Networks in the Subway Station of Workroom. Journal of the Korea Academia-Industrial cooperation Society. 12(7). 3220–3226. 2 indexed citations
4.
Yang, Se-Hyun, et al.. (2010). Comparison of RF Property and Network Property for 802.11n WLAN between In-door and Out-door Environment. Journal of the Korea Academia-Industrial cooperation Society. 11(5). 1702–1707. 1 indexed citations
5.
Cho, Sung Yong, et al.. (2006). Architecture Exploration and Performance Verification Environments of Multi-Core SOC for Mobile Multimedia Embedded Systems. 대한전자공학회 ISOCC. 195–198. 3 indexed citations
6.
Yang, Se-Hyun, et al.. (2005). Accurate and Complexity-Effective Spatial Pattern Prediction. 276–276. 88 indexed citations
7.
Yang, Se-Hyun, Michael D. Powell, Babak Falsafi, & T.N. Vijaykumar. (2004). Exploiting choice in resizable cache design to optimize deep-submicron processor energy-delay. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 151–161. 95 indexed citations
8.
Yang, Se-Hyun & Babak Falsafi. (2004). Near-optimal precharging in high-performance nanoscale CMOS caches. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 67–78. 2 indexed citations
9.
Yang, Se-Hyun & Babak Falsafi. (2003). Near-optimal precharging in high-performance nanoscale CMOS caches. International Symposium on Microarchitecture. 67–78. 7 indexed citations
10.
Yang, Se-Hyun & Babak Falsafi. (2003). Performance and Energy Trade-Offs of Bitline Isolation in Nanoscale CMOS Caches. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
11.
Powell, Michael D., Se-Hyun Yang, Babak Falsafi, Kaushik Roy, & T. N. Vijaykumar. (2002). Gated-V/sub dd/: a circuit technique to reduce leakage in deep-submicron cache memories. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 90–95. 18 indexed citations
12.
Powell, Michael D., Se-Hyun Yang, Babak Falsafi, Kaushik Roy, & T.N. Vijaykumar. (2001). An Energy-Efficient High-Performance Deep-Submicron Instruction Cache. 5 indexed citations
13.
Powell, Michael D., Se-Hyun Yang, Babak Falsafi, Kaushik Roy, & Nandita Vijaykumar. (2001). Reducing leakage in a high-performance deep-submicron instruction cache. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 9(1). 77–89. 61 indexed citations
14.
Powell, Michael D., Se-Hyun Yang, Babak Falsafi, Kaushik Roy, & T. N. Vijaykumar. (2000). Gated-V/sub dd/: a circuit technique to reduce leakage in deep-submicron cache memories. 90–95. 227 indexed citations
15.
Yang, Se-Hyun, Michael D. Powell, Babak Falsafi, Kaushik Roy, & T.N. Vijaykumar. (2000). Dynamically Resizable Instruction Cache: An Energy-Efficient and High-Performance Deep-Submicron Instruction Cache. Purdue e-Pubs (Purdue University System). 4 indexed citations
16.
Yang, Se-Hyun, Michael D. Powell, Babak Falsafi, Kaushik Roy, & T. N. Vijaykumar. (2000). Dynamically Resizable Instruction Cache: A Design for an Energy-Efficient and High-Performance Deep-Submicron Instruction Cache. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
17.
Powell, Michael D., Se-Hyun Yang, Babak Falsafi, Kaushik Roy, & T. N. Vijaykumar. (2000). Gated-Vdd. 90–95. 478 indexed citations breakdown →
18.
Bien, Zeungnam, Dong‐oh Kang, & Se-Hyun Yang. (1999). PROGRAMMING APPROACH FOR FUZZY MODEL-BASED MULTIOBJECTIVE CONTROL SYSTEMS. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 7(4). 293–300. 2 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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