Li-Pin Chang

2.9k total citations
78 papers, 2.2k citations indexed

About

Li-Pin Chang is a scholar working on Computer Networks and Communications, Hardware and Architecture and Electrical and Electronic Engineering. According to data from OpenAlex, Li-Pin Chang has authored 78 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Computer Networks and Communications, 30 papers in Hardware and Architecture and 10 papers in Electrical and Electronic Engineering. Recurrent topics in Li-Pin Chang's work include Advanced Data Storage Technologies (55 papers), Caching and Content Delivery (46 papers) and Parallel Computing and Optimization Techniques (26 papers). Li-Pin Chang is often cited by papers focused on Advanced Data Storage Technologies (55 papers), Caching and Content Delivery (46 papers) and Parallel Computing and Optimization Techniques (26 papers). Li-Pin Chang collaborates with scholars based in Taiwan, United States and China. Li-Pin Chang's co-authors include Tei‐Wei Kuo, Jen-Wei Hsieh, Roy J. Britten, L. Courtney Smith, Eric H. Davidson, Chin-Hsien Wu, S. L. Allman, C. H. Chen, N. I. Taranenko and Kai Tang and has published in prestigious journals such as The Journal of Immunology, IEEE Transactions on Software Engineering and Carcinogenesis.

In The Last Decade

Li-Pin Chang

76 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Li-Pin Chang Taiwan 23 1.6k 798 300 214 212 78 2.2k
Philip J. Hatcher United States 16 333 0.2× 325 0.4× 32 0.1× 67 0.3× 91 0.4× 46 741
Frank Dehne Canada 22 396 0.2× 102 0.1× 338 1.1× 120 0.6× 209 1.0× 119 1.6k
María García de la Banda Australia 19 285 0.2× 100 0.1× 252 0.8× 53 0.2× 463 2.2× 81 1.1k
Weiguo Liu China 17 318 0.2× 236 0.3× 50 0.2× 104 0.5× 325 1.5× 89 1.2k
Ron Y. Pinter Israel 20 215 0.1× 301 0.4× 298 1.0× 26 0.1× 159 0.8× 71 1.8k
Chien‐Hung Huang Taiwan 17 266 0.2× 258 0.3× 234 0.8× 28 0.1× 207 1.0× 76 1.1k
Ion Măndoiu United States 24 297 0.2× 186 0.2× 150 0.5× 6 0.0× 82 0.4× 140 2.2k
Zhiguang Chen China 11 194 0.1× 82 0.1× 17 0.1× 251 1.2× 136 0.6× 91 1.1k
Peter Markstein United States 11 275 0.2× 477 0.6× 368 1.2× 101 0.5× 255 1.2× 22 1.3k
Raffaele Giancarlo Italy 24 214 0.1× 315 0.4× 369 1.2× 165 0.8× 1.1k 5.4× 89 1.7k

Countries citing papers authored by Li-Pin Chang

Since Specialization
Citations

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

Fields of papers citing papers by Li-Pin Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li-Pin Chang. 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 Li-Pin Chang. The network helps show where Li-Pin Chang may publish in the future.

Co-authorship network of co-authors of Li-Pin Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Li-Pin Chang. A scholar is included among the top collaborators of Li-Pin Chang 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 Li-Pin Chang. Li-Pin Chang 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.
Ji, Cheng, et al.. (2021). Memory-efficient deep learning inference with incremental weight loading and data layout reorganization on edge systems. Journal of Systems Architecture. 118. 102183–102183. 13 indexed citations
2.
Chang, Li-Pin, et al.. (2018). Lightweight, Integrated Data Deduplication for Write Stress Reduction of Mobile Flash Storage. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 37(11). 2590–2600. 10 indexed citations
3.
Ji, Cheng, Li-Pin Chang, Sungjin Lee, et al.. (2018). File Fragmentation in Mobile Devices: Measurement, Evaluation, and Treatment. IEEE Transactions on Mobile Computing. 18(9). 2062–2076. 13 indexed citations
4.
Ji, Cheng, et al.. (2017). An I/O Scheduling Strategy for Embedded Flash Storage Devices With Mapping Cache. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 37(4). 756–769. 10 indexed citations
5.
Ji, Cheng, et al.. (2016). An empirical study of file-system fragmentation in mobile storage systems. 76–80. 17 indexed citations
6.
Chang, Li-Pin, et al.. (2016). Eager Synching. ACM Transactions on Embedded Computing Systems. 16(2). 1–25. 5 indexed citations
7.
Chang, Li-Pin. (2014). Design of Data Exchange System for East China Large-scale Dispatching Plan. Dianli xitong zidonghua.
8.
Chang, Li-Pin, et al.. (2014). Reducing asynchrony in channel garbage-collection for improving internal parallelism of multichannel solid-state disks. ACM Transactions on Embedded Computing Systems. 13(2s). 1–23. 10 indexed citations
9.
Chang, Li-Pin, et al.. (2011). Plugging versus logging. 23–28. 12 indexed citations
10.
Chang, Li-Pin, et al.. (2009). Soft lists: a native index structure for NOR-flash-based embedded devices. Asia and South Pacific Design Automation Conference. 799–804. 2 indexed citations
11.
Chang, Li-Pin. (2008). Hybrid solid-state disks: combining heterogeneous NAND flash in large SSDs. Asia and South Pacific Design Automation Conference. 428–433. 73 indexed citations
12.
Chang, Li-Pin & Tei‐Wei Kuo. (2005). Efficient management for large-scale flash-memory storage systems with resource conservation. ACM Transactions on Storage. 1(4). 381–418. 84 indexed citations
13.
Taranenko, N. I., V. V. Golovlev, S. L. Allman, et al.. (1998). Matrix-assisted laser desorption/ionization for short tandem repeat loci. Rapid Communications in Mass Spectrometry. 12(8). 413–418. 22 indexed citations
14.
Taranenko, N. I., Karla J. Matteson, Yifei Zhu, et al.. (1996). Laser desorption mass spectrometry for point mutation detection. Genetic Analysis Biomolecular Engineering. 13(4). 87–94. 23 indexed citations
15.
Smith, L. Courtney, Li-Pin Chang, Roy J. Britten, & Eric H. Davidson. (1996). Sea urchin genes expressed in activated coelomocytes are identified by expressed sequence tags. Complement homologues and other putative immune response genes suggest immune system homology within the deuterostomes. The Journal of Immunology. 156(2). 593–602. 159 indexed citations
16.
Chang, Li-Pin, Maria Schell, Carol S. Ringelberg, et al.. (1995). Detection of ΔF508 mutation of the cystic fibrosis gene by matrix‐assisted laser desorption/ionization mass spectrometry. Rapid Communications in Mass Spectrometry. 9(9). 772–774. 39 indexed citations
17.
Tang, Kai, N. I. Taranenko, S. L. Allman, et al.. (1994). Detection of 500‐nucleotide DNA by laser desorption mass spectrometry. Rapid Communications in Mass Spectrometry. 8(9). 727–730. 66 indexed citations
18.
Tang, Kai, S. L. Allman, C. H. Chen, Li-Pin Chang, & Maria Schell. (1994). Matrix‐assisted laser desorption/ionization of restriction enzyme‐digested DNA. Rapid Communications in Mass Spectrometry. 8(2). 183–186. 27 indexed citations
19.
Taranenko, N. I., Kai Tang, S. L. Allman, Li-Pin Chang, & C. H. Chen. (1994). 3‐aminopicolinic aid as a matrix for laser desorption mass spectrometry of biopolymers. Rapid Communications in Mass Spectrometry. 8(12). 1001–1006. 18 indexed citations
20.

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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