About me

Background

My name is Saraa Aljawad, and I am a PhD student in Bioinformatics at the University of Georgia. My academic background in medical imaging (MRI) and data analysis, with a strong interest in applying computational methods to biomedical data.

My current research focuses on NMR metabolomics, where I study signal-to-noise ratio (SNR), solvent effects, and reproducibility in high-salinity biological samples such as urine. I am particularly interested in building reproducible analysis pipelines and using statistical and machine learning methods to better interpret complex experimental data.

I have experience with:

-MATLAB.

-Python.

Through this course, I hope to strengthen my skills in applied data analysis, improve my ability to design reproducible workflows, and gain more confidence in organizing and communicating complex analyses clearly.

What I Hope to Learn in MADA

In Modern Applied Data Analysis, I am especially interested in learning how to:

• Apply statistical and modeling techniques to real-world datasets
• Build clean, reproducible analysis projects
• Improve code organization and documentation
• Effectively communicate results through reports and websites

A Creative Data Visualization Website

A data visualization website I find interesting is Information Is Beautiful:

https://informationisbeautiful.net

This website presents data through visually striking graphics that combine design and analysis. I find it interesting because it shows how data analysis can be both informative and engaging.