Shuyin Xia

Chongqing University of Posts and Telecommunications · China

Unclaimed · AI-structured profileOpenAlex

Machine learning researcher advancing granular-ball computing from kernel clustering to quantum kernel methods

papers here

reviewed by Evolve

first-author

corresponding

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works · OpenAlex

h-index · OpenAlex

Bibliometric figures come from OpenAlex (2026-10-17) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.

Research profile

Output—

Output is not yet scored: the snapshot lacks sufficient publication-volume data, with OpenAlex h-index and i10-index both reading zero. This axis would measure cumulative paper counts and yearly productivity once a fuller, disambiguated record is linked.

Impact—

Impact is not yet scored: citation-based indicators are missing or read zero in this snapshot, so influence cannot be assessed. This axis would measure citation counts, h-index momentum, and uptake of the granular-ball methods across the clustering and quantum-ML communities.

Focus0/100

The focus axis reads 0. OpenAlex assigns recent works across five topics — Advanced Neural Network Applications (4), Domain Adaptation and Few-Shot Learning (3), Machine Learning and Data Classification (3), Face and Expression Recognition (2), and Image and Video Retrieval (2) — while the field distribution splits evenly (0.5/0.5) between machine learning / quantum machine learning and quantum machine learning, indicating breadth rather than one narrow line.

Collaboration50/100

Collaboration scores 50. The snapshot records 11 distinct coauthors, with recurring partners including Suzhen Yuan, Lifeng Shen, Dehang Chen, and Jeremiah D. Deng. All three 2026 catalog papers are arXiv preprints listing this researcher in a middle author position rather than first or corresponding, consistent with contributing within a team rather than leading every manuscript.

Activity70/100

Activity scores 70, the strongest axis in this profile. OpenAlex records 10 works in the last three years, and the counts-by-year field attributes 10 outputs to 2026 alone. The Evolve catalog independently corroborates this burst, holding three 2026 arXiv preprints on granular-ball clustering and classification from the same publication window.

Reproducibility38/100

Reproducibility scores 38, derived from Evolve's readiness review of 2 papers at a mean of 38. Readiness is uneven: the quantum clustering paper and the kernel-space multiple kernel k-means paper are rated medium — the latter despite missing ablations, runtimes, and restart-variance checks — while the quantum granular-ball kNN is rated low for classical-only simulation and anomalous noise results.

Research summary

Shuyin Xia is a machine learning researcher at Chongqing University of Posts and Telecommunications whose recent work centers on granular-ball computing and its extension into quantum machine learning. The Evolve catalog holds three 2026 arXiv preprints, each listing Xia in a middle author position: GBQC, which uses PCA-guided granular balls to cut quantum-kernel evaluations by roughly 80% and tops clustering benchmarks in simulation; QGB-WkNN, a quantum granular-ball k-nearest-neighbor classifier using purity-guided HNSW and weighted voting for robustness; and DK-GBMKKM, which regenerates granular balls in fused kernel space for multiple kernel k-means and wins across 12 datasets. OpenAlex records 10 works in the last three years, all attributed to 2026, with 11 distinct coauthors. Topic assignments span five areas — advanced neural network applications, domain adaptation and few-shot learning, machine learning and data classification, face and expression recognition, and image and video retrieval — while the field distribution splits evenly between machine learning / quantum machine learning and quantum machine learning. Evolve rates reproducibility readiness at a mean of 38 across 2 reviewed papers, with the quantum kNN preprint rated low. Citation indicators are not yet available, so output and impact remain unscored.

Collaboration pattern

The snapshot records 11 distinct coauthors in the recent window. Recurring partners include Suzhen Yuan, Lifeng Shen, Dehang Chen, and Jeremiah D. Deng, who also appears under the spelling variant 'Jermiah D. Deng', likely a duplicate record. Across the three 2026 catalog papers Shuyin Xia sits in a middle author position without corresponding-author role, suggesting contribution within a granular-ball computing group spanning classical clustering and quantum machine learning rather than sole leadership of each manuscript.

Research keywords

granular-ball computingquantum kernel methodsquantum clusteringmultiple kernel k-meansunsupervised learningk-nearest neighbor classificationapproximate nearest neighbor searchnoise robustnesskernel weight learningspectral embeddingfew-shot learningNISQ algorithms

Highlights

Granular-ball quantum clustering cuts kernel evaluations by ~80%
Evolve's review finds GBQC uses PCA-guided granular balls to prune quantum-kernel evaluations by roughly 80% and win clustering benchmarks in simulation; however, the product-state kernel it relies on remains classically simulable, capping any claimed quantum advantage.
Quantum granular-ball kNN with purity-guided HNSW
QGB-WkNN combines purity-guided HNSW retrieval with weighted voting and shows robustness gains, but Evolve flags classical-only simulation and anomalous noise results as limiting rigor, giving this preprint the catalog's lowest reproducibility readiness.
Dynamic kernel-space granular-ball multiple kernel k-means
DK-GBMKKM regenerates granular balls in the fused kernel space for multiple kernel k-means clustering, with strong wins across 12 datasets and sound theory, though Evolve notes the absence of ablation studies, runtimes, and restart-variance reporting.

Timeline

2026Cataloged preprint GBQC: PCA-guided granular balls cut quantum-kernel evaluations by roughly 80% and top clustering benchmarks in simulation.
2026Co-authored QGB-WkNN, extending granular-ball learning to quantum k-nearest-neighbor classification with purity-guided HNSW and weighted voting.
2026Contributed to DK-GBMKKM, which regenerates granular balls in fused kernel space for multiple kernel k-means, validated across 12 datasets.

Papers in the Evolve catalog

Frequent co-authors

Suzhen Yuan×2 Lifeng Shen×2 Dehang Chen×1 Jeremiah D. Deng×1 Qilin Xie×1 Jermiah D. Deng×1 Guoying Wang×1 Xiaoyu Lian×1 Yuchao Zhang×1 Siqi Zhong×1 Xuzhao Xiang×1

About this profile

This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.

Bibliometric indicators come from OpenAlex only; h-index and i10-index read zero, and the output and impact axes lack sufficient data.
No ORCID is linked; the profile is name-resolved from public bibliographic data and may mix records from authors with the same name.
All three catalog papers are 2026 arXiv preprints; peer-reviewed publication status and citation impact are not yet reflected.
The coauthor list contains a spelling variant ('Jermiah D. Deng'), suggesting duplicate identity records in the underlying data.