Wei-Lin Chiang

1.9k total citations
7 papers, 93 citations indexed

About

Wei-Lin Chiang is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Networks and Communications. According to data from OpenAlex, Wei-Lin Chiang has authored 7 papers receiving a total of 93 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computational Mechanics and 1 paper in Computer Networks and Communications. Recurrent topics in Wei-Lin Chiang's work include Neural Networks and Applications (3 papers), Stochastic Gradient Optimization Techniques (2 papers) and Sparse and Compressive Sensing Techniques (1 paper). Wei-Lin Chiang is often cited by papers focused on Neural Networks and Applications (3 papers), Stochastic Gradient Optimization Techniques (2 papers) and Sparse and Compressive Sensing Techniques (1 paper). Wei-Lin Chiang collaborates with scholars based in Taiwan, United States and Singapore. Wei-Lin Chiang's co-authors include Chih‐Jen Lin, Michael Luo, Zongheng Yang, Ion Stoica, Zhanghao Wu, Scott Shenker, Yusheng Li, Ching-pei Lee, Zhuohan Li and Siyuan Zhuang and has published in prestigious journals such as International Conference on Machine Learning, Proceedings of the 2022 International Conference on Management of Data and Asian Conference on Machine Learning.

In The Last Decade

Wei-Lin Chiang

7 papers receiving 93 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wei-Lin Chiang Taiwan	4	51	30	26	21	20	7	93
Noah A. Smith United States	5	69 1.4×	37 1.2×	8 0.3×	7 0.3×	27 1.4×	11	119
Chris Schwiegelshohn Denmark	5	49 1.0×	20 0.7×	13 0.5×	9 0.4×	25 1.3×	19	77
Jarek Duda Poland	3	40 0.8×	22 0.7×	20 0.8×	5 0.2×	43 2.1×	7	81
Vikram Nitin United States	5	63 1.2×	24 0.8×	6 0.2×	27 1.3×	24 1.2×	6	107
Matthieu Finiasz France	6	76 1.5×	57 1.9×	22 0.8×	9 0.4×	29 1.4×	9	112
Mahesh Motwani India	6	59 1.2×	29 1.0×	11 0.4×	35 1.7×	24 1.2×	19	121
Guillaume Cleuziou France	6	84 1.6×	8 0.3×	22 0.8×	15 0.7×	27 1.4×	11	101
Nicolas Labroche France	6	74 1.5×	11 0.4×	16 0.6×	18 0.9×	29 1.4×	15	92
Prasoon Goyal India	4	81 1.6×	8 0.3×	13 0.5×	8 0.4×	56 2.8×	7	116
Peihan Miao China	6	50 1.0×	18 0.6×	6 0.2×	29 1.4×	37 1.9×	14	97

Countries citing papers authored by Wei-Lin Chiang

Since Specialization

Citations

This map shows the geographic impact of Wei-Lin Chiang'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 Chiang 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 Chiang more than expected).

Fields of papers citing papers by Wei-Lin Chiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei-Lin Chiang

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Wu, Zhanghao, et al.. (2025). SkyServe: Serving AI Models across Regions and Clouds with Spot Instances. 159–175. 1 indexed citations

2.

Chiang, Wei-Lin, et al.. (2023). Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. 46595–46623. 2 indexed citations

3.

Yang, Zongheng, et al.. (2022). Balsa: Learning a Query Optimizer Without Expert Demonstrations. Proceedings of the 2022 International Conference on Management of Data. 931–944. 38 indexed citations

4.

Li, Yusheng, Wei-Lin Chiang, & Ching-pei Lee. (2020). Manifold Identification for Ultimately Communication-Efficient Distributed Optimization. International Conference on Machine Learning. 1. 5842–5852. 1 indexed citations

5.

Chiang, Wei-Lin, et al.. (2018). Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification. Asian Conference on Machine Learning. 312–326. 3 indexed citations

6.

Chiang, Wei-Lin, et al.. (2016). Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments. 1485–1494. 28 indexed citations

7.

Chiang, Wei-Lin, et al.. (2015). Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems. 835–840. 20 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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