CV

Education

• B.S. in Shandong, Shandong University, 2026(excepted)

Research Experience

• Prediction of RNA Modifications using Nanopore Direct RNA Sequencing Reads
• Jun. 2023 – Present:Research Assistant, Research Center of Software and Data Engineering
  • Processed all raw Nanopore Fast5 files, including base calling, re-squiggle operations, and signal-level analysis, with methylation site information fully extracted.
  • Extracted important features for RNA modification data through read alignment and signal segmentation.
  • Conducted site-level analysis of RNA methylation data, achieving accurate prediction of methylation sites.
  • I applied Multi-view Model to improve the accuracy of RNA methylation prediction, achieving a over 5% improvement compared to m6Anet in HEK293T dataset, providing a valuable tool for better predictions.
• Single cell analysis of the impact of age on immune dysregulation and recovery induced by spaceflight
• Jul. 2024 – Present: Research Assistant, Cheeloo College of Medicine
  • Processed the single-cell sequencing data of OSD-402 from NASA GeneLab, completing all single-cell analyses including quality control, clustering, cell type annotation, subgroup annotation, cell communication, and pseudotime analysis.
  • Utilized Seurat, CellChat, monocle3, and other R packages to perform all of the above analyses, and currently in the paper writing stage.
  • The study found that old mice recover more poorly than young mice over the same period of time.
  • This paper is currently in the process of being written.
• Metabolic redundancy of fatty acid desaturation and elongation promotes hypoxia-induced breast cancer stem cell enrichment
• Jul. 2024 – Mar. 2025: Research Assistant, Cheeloo College of Medicine
  • Performed functional analysis such as GO, KEGG, GSEA and GSVA to identify critical pathways influenced by hypoxia.
  • Used the Random Forest algorithm to analyze transcriptomics of hypoxia and normoxia groups, recognizing the hypoxia-associated breast cancer hypoxia signature.
• Prediction of EGFR Mutation Status in Lung Cancer Patients based on Clinical Data
• Sep. 2024 – Present:Research Assistant, Cheeloo College of Medicine
  • Collected and processed multi-modal clinical data, including routine blood test results, CT images, and EGFR mutation status information.
  • Developed an ensemble learning model to predict EGFR mutation status, utilizing algorithms such as Support Vector Machines (SVM), Random Forest and Gradient Descent.
  • Applied cross-validation techniques and predictive performance for model evaluation and validation.
  • Evaluated the performance of the model with dataset from an independent hospital.

Competition

• The Chinese Mathematics Competitions
• Aug. 2022, Second Prize in Shandong Province District
  • This competition assessed the students’ knowledge of advanced mathematics, linear algebra, probability theory, and other related subjects.
• National Professional Software Engineering “Blue Bridge Cup” Design Competitions
• Apr.2024, Third Prize in Shandong Province District
  • This is an algorithm competition that tests the participants’ algorithm and coding skills.

LeadershipRoles

• Chunhui student Volunteer Teaching Club of Shandong University
• Apr. 2023 - Apr. 2024, Campus leader
  • Led various community initiatives, including organizing fundraising events and charity sales, and overseeing volunteer teacher training programs.
  • Established a new volunteer teaching center in Zhangjiajie and successfully completed the first teaching mission in the region.
• School of Software Think Tank, Shandong University
• Apr. 2024 - Present, Head of scientific research department
  • Coordinated research seminars and shared insights on research methodologies and experiences with peers.
  • Compiled and edited a comprehensive orientation guide for incoming freshmen.
  • Organized a 21-day coding challenge to foster continuous learning and engagement among students.

Skills

• Programing Languages:
  • Python
  • C++
  • Java
  • SQL
  • R
• Biology Analysis Expertise:
  • scRNA analysis(primarily using the Seurat and Scanpy)
  • Spatial transcriptomics analysis
  • Machine learning for biology
  • Functional enrichment analysis: GO, KEGG, GSVA, GSEA
  • Clustering and dimensionality reduction techniques for biological data
• Python Packages:
  • Pandas, Matplotlib, Scipy, Numpy, Scanpy, Pandas, pysam, ont-fast5-api, PyTorch, cellpath, Scikit-learn.