Hsin-yi Jiang

453 total citations
12 papers, 291 citations indexed

About

Hsin-yi Jiang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hsin-yi Jiang has authored 12 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hsin-yi Jiang's work include Software Engineering Research (4 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Advanced Software Engineering Methodologies (3 papers). Hsin-yi Jiang is often cited by papers focused on Software Engineering Research (4 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Advanced Software Engineering Methodologies (3 papers). Hsin-yi Jiang collaborates with scholars based in United States, China and Taiwan. Hsin-yi Jiang's co-authors include Carl K. Chang, Wei Zhang, Taiming Feng, Dan Zhu, Yujia Ge, Hua Ming, Katsunori Oyama, Tien N. Nguyen, Hen‐I Yang and Wei Zhang and has published in prestigious journals such as Information and Software Technology and IEEE Transactions on Services Computing.

In The Last Decade

Hsin-yi Jiang

11 papers receiving 262 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hsin-yi Jiang United States	7	229	99	91	66	54	12	291
Rob Pooley United Kingdom	9	173 0.8×	139 1.4×	76 0.8×	90 1.4×	32 0.6×	28	327
Radziah Mohamad Malaysia	10	227 1.0×	113 1.1×	101 1.1×	117 1.8×	24 0.4×	53	342
Martín Garriga Argentina	10	274 1.2×	129 1.3×	189 2.1×	42 0.6×	26 0.5×	24	369
Jeff McAffer United States	6	113 0.5×	95 1.0×	104 1.1×	47 0.7×	17 0.3×	14	246
Mahmoud Nassar Morocco	9	164 0.7×	130 1.3×	73 0.8×	84 1.3×	24 0.4×	74	277
Ray Paul United States	11	204 0.9×	98 1.0×	145 1.6×	40 0.6×	46 0.9×	15	273
Elder Cirilo Brazil	10	224 1.0×	137 1.4×	117 1.3×	87 1.3×	13 0.2×	40	286
Anna Maria Vollmer Germany	9	218 1.0×	80 0.8×	73 0.8×	85 1.3×	16 0.3×	12	330
Mohammad Abdallah Jordan	10	214 0.9×	152 1.5×	56 0.6×	54 0.8×	24 0.4×	50	352
Antonio Maña Spain	12	249 1.1×	209 2.1×	165 1.8×	21 0.3×	27 0.5×	70	430

Countries citing papers authored by Hsin-yi Jiang

Since Specialization

Citations

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

Fields of papers citing papers by Hsin-yi Jiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin-yi Jiang. 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 Hsin-yi Jiang. The network helps show where Hsin-yi Jiang may publish in the future.

Co-authorship network of co-authors of Hsin-yi Jiang

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

All Works

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12 of 12 papers shown

1.

Chang, Carl K., et al.. (2012). Automated Web Service Composition Using Genetic Programming. 40. 7–12. 7 indexed citations

2.

Yang, Hen‐I, et al.. (2012). Automatic Data Clustering Analysis of Arbitrary Shape with K-Means and Enhanced Ant-Based Template Mechanism. 452–460. 4 indexed citations

3.

Zhang, Wei, Carl K. Chang, Hen‐I Yang, & Hsin-yi Jiang. (2010). A Hybrid Approach to Data Clustering Analysis with K-Means and Enhanced Ant-Based Template Mechanism. 390–397. 4 indexed citations

4.

Zhang, Wei, Carl K. Chang, Taiming Feng, & Hsin-yi Jiang. (2010). QoS-Based Dynamic Web Service Composition with Ant Colony Optimization. 493–502. 84 indexed citations

5.

Chang, Carl K., Hsin-yi Jiang, Hua Ming, & Katsunori Oyama. (2009). Situ: A Situation-Theoretic Approach to Context-Aware Service Evolution. IEEE Transactions on Services Computing. 2(3). 261–275. 51 indexed citations

6.

Jiang, Hsin-yi & Carl K. Chang. (2008). Deriving evaluation metrics for applicability of genetic algorithms to optimization problems. 1113–1114. 2 indexed citations

7.

Jiang, Hsin-yi, et al.. (2008). Incremental Latent Semantic Indexing for Automatic Traceability Link Evolution Management. 59–68. 44 indexed citations

8.

Chang, Carl K., et al.. (2008). Time-line based model for software project scheduling with genetic algorithms. Information and Software Technology. 50(11). 1142–1154. 69 indexed citations

9.

Jiang, Hsin-yi, et al.. (2007). A History-Based Automatic Scheduling Model for Personnel Risk Management. 2. 361–366. 5 indexed citations

10.

Jiang, Hsin-yi, et al.. (2007). A foundational study on the applicability of genetic algorithm to software engineering problems. 2210–2219. 9 indexed citations

11.

Jiang, Hsin-yi, et al.. (2007). Traceability Link Evolution Management with Incremental Latent Semantic Indexing. 309–316. 5 indexed citations

12.

Jiang, Hsin-yi. (2006). Can the Genetic Algorithm Be a Good Tool for Software Engineering Searching Problems?. 362–366. 7 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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