Gu-Yeon Wei

12.0k total citations · 4 hit papers
228 papers, 8.1k citations indexed

About

Gu-Yeon Wei is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Computer Networks and Communications. According to data from OpenAlex, Gu-Yeon Wei has authored 228 papers receiving a total of 8.1k indexed citations (citations by other indexed papers that have themselves been cited), including 150 papers in Electrical and Electronic Engineering, 101 papers in Hardware and Architecture and 65 papers in Computer Networks and Communications. Recurrent topics in Gu-Yeon Wei's work include Parallel Computing and Optimization Techniques (82 papers), Low-power high-performance VLSI design (58 papers) and Embedded Systems Design Techniques (37 papers). Gu-Yeon Wei is often cited by papers focused on Parallel Computing and Optimization Techniques (82 papers), Low-power high-performance VLSI design (58 papers) and Embedded Systems Design Techniques (37 papers). Gu-Yeon Wei collaborates with scholars based in United States, United Kingdom and South Korea. Gu-Yeon Wei's co-authors include David Brooks, Wonyoung Kim, Meeta S. Gupta, Brandon Reagen, Sae Kyu Lee, Xiaoyao Liang, Michael Karpelson, Mark Horowitz, David J. Brooks and Robert J. Wood and has published in prestigious journals such as Communications of the ACM, IEEE Transactions on Power Electronics and IEEE Journal of Solid-State Circuits.

In The Last Decade

Gu-Yeon Wei

220 papers receiving 7.8k citations

Hit Papers

System level analysis of fast, per-core DVFS using on-chi... 2007 2026 2013 2019 2008 2007 2015 2014 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gu-Yeon Wei United States 49 4.9k 3.3k 2.7k 1.1k 920 228 8.1k
Tajana Rosing United States 47 4.7k 1.0× 2.7k 0.8× 3.0k 1.1× 281 0.3× 1.1k 1.2× 299 7.6k
David Brooks United States 52 6.9k 1.4× 7.7k 2.3× 5.3k 2.0× 374 0.3× 1.1k 1.2× 227 11.9k
Francky Catthoor Belgium 46 5.5k 1.1× 5.5k 1.7× 4.9k 1.8× 513 0.5× 1.0k 1.1× 892 11.3k
Muhammad Shafique Germany 42 4.1k 0.8× 3.2k 1.0× 2.2k 0.8× 354 0.3× 1.0k 1.1× 448 7.3k
Sandeep K. S. Gupta United States 40 1.6k 0.3× 1.3k 0.4× 3.0k 1.1× 902 0.8× 463 0.5× 207 5.5k
Anand Raghunathan United States 61 8.4k 1.7× 6.1k 1.9× 4.5k 1.7× 1.4k 1.2× 2.4k 2.6× 400 14.0k
Jörg Henkel Germany 42 4.9k 1.0× 5.2k 1.6× 3.7k 1.4× 323 0.3× 739 0.8× 546 9.1k
Diana Marculescu United States 39 3.6k 0.7× 3.1k 1.0× 1.9k 0.7× 376 0.3× 504 0.5× 246 5.6k
Bashir M. Al‐Hashimi United Kingdom 39 4.1k 0.8× 2.6k 0.8× 2.0k 0.7× 652 0.6× 321 0.3× 337 5.6k
Dennis Sylvester United States 71 16.6k 3.4× 5.6k 1.7× 3.0k 1.1× 4.4k 4.0× 774 0.8× 602 19.0k

Countries citing papers authored by Gu-Yeon Wei

Since Specialization
Citations

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

Fields of papers citing papers by Gu-Yeon Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gu-Yeon Wei. 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 Gu-Yeon Wei. The network helps show where Gu-Yeon Wei may publish in the future.

Co-authorship network of co-authors of Gu-Yeon Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Gu-Yeon Wei. A scholar is included among the top collaborators of Gu-Yeon Wei 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 Gu-Yeon Wei. Gu-Yeon Wei 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.
Acun, Bilge, Newsha Ardalani, Zachary DeVito, et al.. (2024). MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. 818–833. 2 indexed citations
3.
Carmean, Doug, Ramesh Peri, Srilatha Manne, et al.. (2023). Carbon-Efficient Design Optimization for Computing Systems. 1–7. 11 indexed citations
4.
Rama, Saketh, et al.. (2022). Early DSE and Automatic Generation of Coarse-grained Merged Accelerators. ACM Transactions on Embedded Computing Systems. 22(2). 1–29. 5 indexed citations
5.
Krishnan, Srivatsan, Zishen Wan, Kshitij Bhardwaj, et al.. (2022). Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles. 300–317. 27 indexed citations
6.
Tambe, Thierry, En-Yu Yang, Coleman Hooper, et al.. (2022). A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs. IEEE Journal of Solid-State Circuits. 58(2). 569–581. 12 indexed citations
7.
Lee, Sae Kyu, et al.. (2021). SMIV: A 16-nm 25-mm² SoC for IoT With Arm Cortex-A53, eFPGA, and Coherent Accelerators. IEEE Journal of Solid-State Circuits. 57(2). 639–650. 13 indexed citations
8.
Brooks, David, et al.. (2019). A binary-activation, multi-level weight RNN and training algorithm for processing-in-memory inference with eNVM. arXiv (Cornell University). 1 indexed citations
9.
Whatmough, Paul N., Sae Kyu Lee, David Brooks, & Gu-Yeon Wei. (2018). DNN Engine: A 28-nm Timing-Error Tolerant Sparse Deep Neural Network Processor for IoT Applications. IEEE Journal of Solid-State Circuits. 53(9). 2722–2731. 69 indexed citations
10.
Brooks, David, et al.. (2017). An Area-Efficient 8-Bit Single-Ended ADC With Extended Input Voltage Range. IEEE Transactions on Circuits & Systems II Express Briefs. 65(11). 1549–1553. 8 indexed citations
11.
Lee, Sae Kyu, et al.. (2016). A 16-Core Voltage-Stacked System With Adaptive Clocking and an Integrated Switched-Capacitor DC–DC Converter. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 25(4). 1271–1284. 18 indexed citations
12.
Shao, Yakun Sophia, Sam Likun Xi, Vijayalakshmi Srinivasan, Gu-Yeon Wei, & David Brooks. (2016). Co-designing accelerators and SoC interfaces using gem5-Aladdin. 1–12. 71 indexed citations
13.
Shao, Yakun Sophia, Brandon Reagen, Gu-Yeon Wei, & David Brooks. (2014). Aladdin: A pre-RTL, power-performance accelerator simulator enabling large design space exploration of customized architectures. 97–108. 89 indexed citations
14.
Reagen, Brandon, Yakun Sophia Shao, Gu-Yeon Wei, & David Brooks. (2013). Quantifying acceleration: power/performance trade-offs of application kernels in hardware. 395–400. 7 indexed citations
15.
Zhang, Xuan, et al.. (2013). Characterizing and evaluating voltage noise in multi-core near-threshold processors. 82–87. 20 indexed citations
16.
Rangan, Krishna K., Michael D. Powell, Gu-Yeon Wei, & David Brooks. (2011). Achieving uniform performance and maximizing throughput in the presence of heterogeneity. 3–14. 27 indexed citations
17.
Gupta, Meeta S., Vijay Janapa Reddi, Glenn Holloway, Gu-Yeon Wei, & David Brooks. (2009). An event-guided approach to reducing voltage noise in processors. Design, Automation, and Test in Europe. 160–165. 29 indexed citations
18.
Liang, Xiaoyao, Ramón Canal, Gu-Yeon Wei, & David Brooks. (2008). R 6T SRAM 3T1D DRAM L1 D C C P V. UPCommons institutional repository (Universitat Politècnica de Catalunya). 28(1). 60–68. 24 indexed citations
19.
Wei, Gu-Yeon, et al.. (2008). Evaluation of voltage interpolation to address process variations. International Conference on Computer Aided Design. 529–536. 3 indexed citations
20.
Hanumolu, Pavan Kumar, et al.. (2004). Jitter in high-speed serial and parallel links. IV–425. 4 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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