# Shengzhou Li

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/shengzhou-li/

## Facts

| Field | Value |
| --- | --- |
| Citations | 268 |
| Field | Machine Learning in Materials Science |
| h-index | 10 |
| i10-index | 10 |
| Last Known Institution | University of Tsukuba |
| OpenAlex ID | https://openalex.org/A5103024387 |
| ORCID iD | 0000-0001-6973-3825 |
| Works | 49 |

## Researcher papers

- [Study on the factors affecting solid solubility in binary alloys: An exploration by Machine Learning](https://scholariq.org/papers/study-on-the-factors-affecting-solid-solubility-in-binary-alloys-an-exploration/)
- [Sensitization Strategies of Lateral Flow Immunochromatography for Gold Modified Nanomaterials in Biosensor Development](https://scholariq.org/papers/sensitization-strategies-of-lateral-flow-immunochromatography-for-gold-modified/)
- [The Role of Hepatic Arterial Infusion Chemotherapy in the Treatment of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis](https://scholariq.org/papers/the-role-of-hepatic-arterial-infusion-chemotherapy-in-the-treatment-of/)
- [PD-YOLO: a novel weed detection method based on multi-scale feature fusion](https://scholariq.org/papers/pd-yolo-a-novel-weed-detection-method-based-on-multi-scale-feature-fusion/)
- [Synergistic enhancement of chemotherapy for bladder cancer by photothermal dual-sensitive nanosystem with gold nanoparticles and PNIPAM](https://scholariq.org/papers/synergistic-enhancement-of-chemotherapy-for-bladder-cancer-by-photothermal-dual/)
- [A domain knowledge enhanced machine learning method to predict the properties of halide double perovskite A <sub>2</sub> B <sup>+</sup> B <sup>3+</sup> X <sub>6</sub>](https://scholariq.org/papers/a-domain-knowledge-enhanced-machine-learning-method-to-predict-the-properties-of/)
- [An end-to-end machine learning framework exploring phase formation for high entropy alloys](https://scholariq.org/papers/an-end-to-end-machine-learning-framework-exploring-phase-formation-for-high/)
- [VMamba for plant leaf disease identification: design and experiment](https://scholariq.org/papers/vmamba-for-plant-leaf-disease-identification-design-and-experiment/)
- [An in-situ gold growth self-catalytic signal amplification system enhanced hollow gold immunochromatography for ultrasensitive detection of p24 antigen in HIV infection](https://scholariq.org/papers/an-in-situ-gold-growth-self-catalytic-signal-amplification-system-enhanced/)
- [Prediction of superconducting transition temperature using a machine-learning method](https://scholariq.org/papers/prediction-of-superconducting-transition-temperature-using-a-machine-learning/)

## Researcher topics

- [Machine Learning in Materials Science](https://scholariq.org/topics/machine-learning-in-materials-science/)
- [Advanced Nanomaterials in Catalysis](https://scholariq.org/topics/advanced-nanomaterials-in-catalysis/)
- [Advanced biosensing and bioanalysis techniques](https://scholariq.org/topics/advanced-biosensing-and-bioanalysis-techniques/)

## Researcher university

- [University of Tsukuba](https://scholariq.org/institutions/university-of-tsukuba/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.