河南工业大学 | 生物工程学院 & 信息科学与工程学院 · 生物工程（主修） & 计算机科学与技术（辅修） | 本科大二在读
一名具备 “生物+计算”交叉学科背景 的大二学生。主修生物工程，系统掌握现代生物学原理；辅修计算机科学，熟练运用编程与算法解决工程问题。对 计算生物学、生物信息学及高性能计算在生命科学中的应用 充满热情。通过个人博客持续实践并分享 生物数据挖掘、生物计算加速（CUDA）及分析流程开发 等项目，致力于搭建连接生物问题与计算解决方案的桥梁。
Personal Profile: An explorer with an interdisciplinary background in "Biology + Computing". Majoring in Biological Engineering, I have systematically mastered modern biological principles; minoring in Computer Science, I am proficient in using programming and algorithms to solve engineering problems. Passionate about computational biology, bioinformatics, and the application of high-performance computing in life sciences, I continuously practice and share projects such as biological data mining (e.g., WGCNA), accelerated biological computing (CUDA), and analysis pipeline development through my personal blog, striving to build a bridge connecting biological problems with computational solutions.
相关课程：生物学核心：生物化学、分子生物学、基因工程、细胞生物学；计算与信息核心：Python/C++程序设计、数据结构、算法基础、数据库原理。
Education Background: Henan University of Technology (Expected 2028) - Major: Biological Engineering, Minor: Computer Science. GPA 3.6/4.0. Core coursework includes Biochemistry, Molecular Biology, Genetic Engineering, Python/C++ Programming, Data Structures, Algorithms, etc.
| 🧬 生物信息学与数据分析 | WGCNA、差异表达分析、GO/KEGG富集分析、R语言（tidyverse, ggplot2）、Bioconductor基础、NCBI工具集、分子对接、动力学模拟 |
|---|---|
| ⚡ 编程与高性能计算 | Python (NumPy, Pandas, Scikit-learn)、C/C++、CUDA并行编程入门、Linux命令行、Shell脚本 |
| 🌐 全栈开发与自动化 | 前端：HTML/CSS/JavaScript (Vue.js基础)；后端：Python Flask/Node.js；数据库：MySQL；流程自动化脚本编写 |
| 🔬 生物实验与软件 | 熟悉常规分子实验原理、ImageJ、PyMOL(基础)、SnapGene、GraphPad Prism |
| 🛠️ 通用工具 | Git、Docker（基础）、VS Code、Jupyter Notebook、Markdown |
Computational Biology Project: WGCNA-based gene co-expression network construction and phenotype correlation analysis (Nov-Dec 2024). Completed end-to-end analysis and published a detailed tutorial.
Interdisciplinary Project: Preliminary exploration of temperature field acceleration using CUDA (Dec 2024 - present). Achieved ~22x speedup over CPU.
Tool Development: C++ program for radius-weighted center analysis of protein-ligand binding sites (Oct 2024). Self-developed PDB parser and weighting algorithm.
拥有计算机和生物学基础：从生物工程的本源理解生命科学的复杂问题，从计算机科学的手段寻找高效、精准的解决方案。我享受这种在湿实验（Wet Lab）与干实验（Dry Lab）之间穿梭的挑战。具备自主学习能力、逻辑思维能力和将复杂问题工程化的能力。渴望在合成生物学、计算生物、生物信息或药物发现等领域，从事将前沿生物问题与先进计算技术相结合的实习或科研工作。
Summary: Possess a dual perspective, enjoy navigating between Wet Lab and Dry Lab. Strong self-learning and logical reasoning skills. Eager to pursue internships/research in synthetic biology, computational biology, bioinformatics, or drug discovery.