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👋 Hi there, I'm Xingcheng Ni

🚀 Researcher | Developer | Aspiring Bioinformatician | Future PhD (hopefully!)


🌟 About Me

  • 🎓 PhD student (0th year) at the University of Chinese Academy of Sciences, Shanghai Institute of Nutrition and Health.
  • 🔬 My research focuses on Computational Biology, where I explore how data-driven methods can unlock the secrets of biological systems and advance healthcare.
  • 🧬 If I am not dealing with algorithms, I am busy trying to solve math problems and making sense of the universe (or at least trying to!).
  • 🤖 Exploring the fascinating worlds of Statistics, Probability, and the ever-growing field of Machine Learning and Deep Learning.
  • ✍️ Passionate about mathematical foundations that power algorithms, and sharing my journey through open-source projects on GitHub.

📊 My GitHub Stats

GitHub Stats

Top Langs

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🛠️ Tools & Tech I Use

🔥 Languages:

Python R Shell

🛠️ Tools:

LaTeX Markdown Quarto Git

💡 Learning:

MySQL C++


✨ Featured Projects

  • 🔗 math - A love letter to my undergraduate years: I’m compiling all the knowledge I learned, filling in missing details from textbooks, and trying to present it all in a more logical, organized manner. Currently, it’s a LaTeX project—no PDFs, so get ready to compile it yourself!
  • 💹 stock - The world of stocks, simplified: A modest start to a journey with my friend in the stock market. It’s a work in progress, but who knows, one day we might just become stock market moguls! 💰💸
  • 🧬 MLAS - The code from my first published paper in Horticulturae! We used computational methods to find genes in Chinese cabbage that could potentially respond to abiotic stresses (cold, heat, salt, and drought).
  • 🤖 BERT - From scratch, with love: A fully custom BERT model using PyTorch, just the Masked Language Model (MLM) task for now. Because sometimes you just need to build things yourself, right?
  • 📊 sampling-method - Turning sampling surveys into something more than just class notes: I transformed my lecture notes into a clean LaTeX-coded PDF, with code for practical applications. A neat little guide for anyone who’s curious about statistical sampling methods! 👉 You’d better check out the sampling survey section in my math repo, where I’ve updated and expanded on it with more details and fresh insights!

🧠 Let’s Chat!

If you’re into computational biology, statistics, probability, machine learning, deep learning, or if you just want to geek out over algorithms (or maybe discuss your latest paper), hit me up! 🚀
Whether it’s coding, research, or life—let’s chat about how we can push the limits of what’s possible! 😜
📧 Email: nxcexpect@163.com

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