Bei Yu

8.7k total citations · 2 hit papers
394 papers, 5.5k citations indexed

About

Bei Yu is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Artificial Intelligence. According to data from OpenAlex, Bei Yu has authored 394 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 281 papers in Electrical and Electronic Engineering, 126 papers in Hardware and Architecture and 75 papers in Artificial Intelligence. Recurrent topics in Bei Yu's work include Advancements in Photolithography Techniques (141 papers), VLSI and FPGA Design Techniques (115 papers) and VLSI and Analog Circuit Testing (76 papers). Bei Yu is often cited by papers focused on Advancements in Photolithography Techniques (141 papers), VLSI and FPGA Design Techniques (115 papers) and VLSI and Analog Circuit Testing (76 papers). Bei Yu collaborates with scholars based in Hong Kong, China and United States. Bei Yu's co-authors include David Z. Pan, Yuzhe Ma, Haoyu Yang, Evangeline F. Y. Young, Jhih-Rong Gao, Tinghuan Chen, Yibo Lin, Xiaoqing Xu, Qi Sun and Tetsuaki Matsunawa and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Hazardous Materials and The Journal of the Acoustical Society of America.

In The Last Decade

Bei Yu

350 papers receiving 5.4k citations

Hit Papers

Recent advances in convolutional neural network acceleration 2018 2026 2020 2023 2018 2024 100 200 300
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. Recent advances in convolutional neural network acceleration
    2018 302 citations Tinghuan Chen, Yuzhe Ma et al. profile →
  2. ChatEDA: A Large Language Model Powered Autonomous Agent for EDA
    2024 51 citations Zhuolun He, Bei Yu et al. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bei Yu Hong Kong 35 3.7k 1.7k 1.0k 982 953 394 5.5k
David Z. Pan United States 51 9.4k 2.6× 4.4k 2.6× 546 0.5× 1.4k 1.5× 797 0.8× 569 10.9k
Rob A. Rutenbar United States 42 5.3k 1.4× 3.2k 1.9× 260 0.3× 1.1k 1.1× 304 0.3× 215 7.0k
Huazhong Yang China 48 7.1k 1.9× 1.9k 1.1× 2.9k 2.8× 2.1k 2.1× 134 0.1× 619 10.5k
Sparsh Mittal India 34 2.4k 0.6× 1.9k 1.1× 876 0.9× 765 0.8× 115 0.1× 145 4.8k
Martin D. F. Wong United States 46 8.2k 2.3× 5.1k 3.0× 419 0.4× 535 0.5× 751 0.8× 545 9.7k
Fan Yang China 27 1.2k 0.3× 378 0.2× 1.5k 1.5× 741 0.8× 178 0.2× 225 3.6k
Jason Cong United States 54 6.9k 1.9× 6.9k 4.0× 2.5k 2.5× 1.8k 1.8× 192 0.2× 404 12.4k
Sen Wang China 34 1.5k 0.4× 261 0.2× 1.3k 1.3× 606 0.6× 93 0.1× 167 4.1k
Carlo H. Séquin United States 31 934 0.3× 439 0.3× 1.5k 1.4× 341 0.3× 333 0.3× 204 4.6k
Chaitali Chakrabarti United States 36 2.4k 0.6× 1.7k 1.0× 1.3k 1.3× 737 0.8× 56 0.1× 287 5.1k

Countries citing papers authored by Bei Yu

Since Specialization
Citations

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

Fields of papers citing papers by Bei Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bei Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Bei Yu. A scholar is included among the top collaborators of Bei Yu 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 Bei Yu. Bei Yu 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.
Chen, Tinghuan, et al.. (2025). IncreMacro: Incremental Macro Placement Refinement. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(8). 3222–3235.
2.
He, Zhuolun, et al.. (2025). Customized Retrieval Augmented Generation and Benchmarking for EDA Tool Documentation QA. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(12). 4615–4628.
3.
Chen, Song, et al.. (2025). PRO-TIME: Prerouting Optimization-Aware Timing Prediction via Multimodal Learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(12). 4779–4792.
4.
5.
6.
Zheng, Xin, et al.. (2025). Efficient Design Space Exploration for the BOOM Using SAC-Based Reinforcement Learning. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 33(8). 2252–2263.
7.
8.
Zhao, Wenqian, et al.. (2024). ChatPattern: Layout Pattern Customization via Natural Language. 1–6. 3 indexed citations
9.
Xu, Qi, et al.. (2024). Floorplanning with Edge-aware Graph Attention Network and Hindsight Experience Replay. ACM Transactions on Design Automation of Electronic Systems. 29(3). 1–17. 1 indexed citations
10.
Wei, Xuechao, Youwei Zhuo, Yi Cai, et al.. (2024). Klotski v2: Improved DNN Model Orchestration Framework for Dataflow Architecture Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(3). 1045–1058. 1 indexed citations
11.
Liao, Peiyu, Junhua Huang, Hui‐Ling Zhen, et al.. (2024). Parallel Gröbner Basis Rewriting and Memory Optimization for Efficient Multiplier Verification. 1–6. 1 indexed citations
12.
Lin, Wei, et al.. (2024). Fed2Com: Towards Efficient Compression in Federated Learning. 3. 560–566.
13.
Yu, Bei, et al.. (2023). MeHLDT: A multielement hash lock data transfer mechanism for on-chain and off-chain. Peer-to-Peer Networking and Applications. 16(4). 1927–1943. 3 indexed citations
14.
Zhao, Wenqian, et al.. (2023). Bit-Level Quantization for Efficient Layout Hotspot Detection. 465–470. 2 indexed citations
15.
Cui, Jiequan, et al.. (2023). Generalized Parametric Contrastive Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 7463–7474. 32 indexed citations
16.
Rapp, Martin, Hussam Amrouch, Yibo Lin, et al.. (2021). MLCAD: A Survey of Research in Machine Learning for CAD Keynote Paper. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(10). 3162–3181. 60 indexed citations
17.
Yang, Haoyu, Wei Zhong, Yuzhe Ma, et al.. (2020). VLSI Mask Optimization: From Shallow To Deep Learning. 434–439. 6 indexed citations
18.
Ma, Yuzhe, Ran Chen, Wei Li, et al.. (2019). A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 376–383. 8 indexed citations
19.
Pui, Chak-Wa, Gengjie Chen, Yuzhe Ma, Evangeline F. Y. Young, & Bei Yu. (2017). Clock-aware ultrascale FPGA placement with machine learning routability prediction. International Conference on Computer Aided Design. 21 indexed citations
20.
Yu, Bei, Sheqin Dong, Song Chen, & Satoshi Goto. (2010). Floorplanning and topology generation for application-specific network-on-chip. arXiv (Cornell University). 535–540. 32 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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