Wei Lin

3.2k total citations · 1 hit paper
81 papers, 1.9k citations indexed

About

Wei Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Wei Lin has authored 81 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 33 papers in Computer Vision and Pattern Recognition and 26 papers in Information Systems. Recurrent topics in Wei Lin's work include Advanced Neural Network Applications (18 papers), Cloud Computing and Resource Management (16 papers) and Parallel Computing and Optimization Techniques (15 papers). Wei Lin is often cited by papers focused on Advanced Neural Network Applications (18 papers), Cloud Computing and Resource Management (16 papers) and Parallel Computing and Optimization Techniques (15 papers). Wei Lin collaborates with scholars based in China, United States and Hong Kong. Wei Lin's co-authors include Lidong Zhou, Fan Li, Pei Cao, Quinn Jacobson, Jingren Zhou, Jingren Zhou, Zhengping Qian, Éric Boutin, Bing Shi and Ming Wu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Biomechanics.

In The Last Decade

Wei Lin

72 papers receiving 1.8k citations

Hit Papers

Apollo: scalable and coordinated scheduling for cloud-sca... 2014 2026 2018 2022 2014 50 100 150 200
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. Apollo: scalable and coordinated scheduling for cloud-scale computing
    2014 214 citations Éric Boutin, Jaliya Ekanayake et al. Operating Systems Design and Implementation profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wei Lin China 22 912 702 645 635 239 81 1.9k
Yuxiong He United States 26 1.1k 1.2× 745 1.1× 723 1.1× 928 1.5× 545 2.3× 86 2.4k
Jidong Zhai China 23 959 1.1× 518 0.7× 443 0.7× 543 0.9× 611 2.6× 120 1.6k
Seong Oun Hwang South Korea 22 409 0.4× 491 0.7× 772 1.2× 804 1.3× 69 0.3× 155 1.8k
Liang Xiong China 14 331 0.4× 478 0.7× 299 0.5× 543 0.9× 116 0.5× 38 1.3k
Zhenhua Liu United States 18 1.2k 1.3× 920 1.3× 290 0.4× 277 0.4× 157 0.7× 81 1.9k
Renyu Yang China 22 945 1.0× 802 1.1× 256 0.4× 681 1.1× 53 0.2× 66 1.8k
Xiaofei Liao China 25 2.6k 2.9× 1.4k 2.0× 800 1.2× 611 1.0× 645 2.7× 314 3.6k
Yongwei Wu China 24 1.3k 1.5× 848 1.2× 354 0.5× 384 0.6× 565 2.4× 130 1.8k
Matthieu Devin United States 5 382 0.4× 202 0.3× 959 1.5× 1.6k 2.5× 140 0.6× 6 2.4k
Chen Feng Canada 22 1.1k 1.2× 811 1.2× 209 0.3× 280 0.4× 121 0.5× 109 2.0k

Countries citing papers authored by Wei Lin

Since Specialization
Citations

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

Fields of papers citing papers by Wei Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Lin. A scholar is included among the top collaborators of Wei Lin 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 Wei Lin. Wei Lin 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, Quan, et al.. (2025). Improving GPU Sharing Performance through Adaptive Bubbleless Spatial-Temporal Sharing. 573–588. 2 indexed citations
2.
Wang, Yejing, Xiangyu Zhao, Qidong Liu, et al.. (2025). Behavior Modeling Space Reconstruction for E-Commerce Search. 1683–1692.
3.
Zhou, Yangjie, Jingwen Leng, Zihan Liu, et al.. (2025). Voyager: Input-Adaptive Algebraic Transformations for High-Performance Graph Neural Networks. 247–263.
4.
Wang, Zeke, et al.. (2025). Helios: Efficient Distributed Dynamic Graph Sampling for Online GNN Inference. 2–15. 3 indexed citations
5.
Lin, Wei, et al.. (2025). A lightweight hyperspectral image multi-layer feature fusion classification method based on spatial and channel reconstruction. PLoS ONE. 20(5). e0322345–e0322345. 1 indexed citations
6.
7.
Cai, Zhenkun, Xiao Yan, Yang Zhang, et al.. (2024). PPS: Fair and efficient black-box scheduling for multi-tenant GPU clusters. Parallel Computing. 120. 103082–103082. 1 indexed citations
8.
Yang, Zhi, et al.. (2023). GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning. Proceedings of the ACM on Management of Data. 1(2). 1–25. 7 indexed citations
9.
Xiao, Wencong, Hailong Yang, Zhongzhi Luan, et al.. (2023). EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs. 1–14. 4 indexed citations
10.
Zheng, Zhen, Feng Zhang, Ruofan Wu, et al.. (2023). RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns. 268–286. 1 indexed citations
11.
Zheng, Zhen, et al.. (2023). BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach. Proceedings of the ACM on Management of Data. 1(3). 1–29. 4 indexed citations
12.
Cheema, Muhammad Jehanzeb Masud, et al.. (2022). Delineation of nutrient management zones for precise fertilizer management in wheat crop using geo‐statistical techniques. Soil Use and Management. 38(3). 1430–1445. 16 indexed citations
13.
An, Yang, Junyang Lin, Rui Men, et al.. (2021). Exploring Sparse Expert Models and Beyond. arXiv (Cornell University). 4 indexed citations
14.
Xiao, Wencong, Yong Li, Yang Zhang, et al.. (2020). AntMan: Dynamic Scaling on GPU Clusters for Deep Learning.. Operating Systems Design and Implementation. 533–548. 22 indexed citations
15.
Zhu, Rong, Kun Zhao, Hongxia Yang, et al.. (2019). AliGraph. Proceedings of the VLDB Endowment. 12(12). 2094–2105. 179 indexed citations
16.
Lin, Wei, et al.. (2016). STREAMSCOPE: continuous reliable distributed processing of big data streams. Networked Systems Design and Implementation. 439–453. 46 indexed citations
17.
Boutin, Éric, Jaliya Ekanayake, Wei Lin, et al.. (2014). Apollo: scalable and coordinated scheduling for cloud-scale computing. Operating Systems Design and Implementation. 285–300. 214 indexed citations breakdown →
18.
Lin, Wei & K. B. Kulasekera. (2009). Testing the equality of linear single-index models. Journal of Multivariate Analysis. 101(5). 1156–1167. 2 indexed citations
19.
Lü, Zhe, et al.. (2009). Models of maximum stress and strain of zebrafish embryos under indentation. Journal of Biomechanics. 42(5). 620–625. 17 indexed citations
20.
Liu, Xuezheng, Wei Lin, Aimin Pan, & Zheng Zhang. (2007). WiDS checker: combating bugs in distributed systems. Networked Systems Design and Implementation. 19–19. 63 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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