Making sense of complexity through data. Leveraging AI to empower people and decisions.
This portfolio captures my journey from data analytics to machine learning. I began with projects in R and soon transitioned to Python, where I discovered the world of AI. Along the way, I've learned to build models catering to supervised and unsupervised learning. I'm currently getting more familiar with deep learning—specifically computer vision and retrieval-augmented generation. Check out some of my work here.
This section showcases hands-on projects where I apply Python and R to solve real-world problems. From data cleaning to model evaluation, each project includes a clear data pipeline, code snippets, and key takeaways. You'll also find notes on the challenges I faced and how I overcame them, offering insight into my problem-solving approach.
Select a project from the project list to load the full write-up.
I am an aspiring data scientist and educator focused on curriculum innovation, AI-driven assessment, and machine learning for real-world educational impact. I attained my BSc in Liberal Arts & Sciences from Maastricht University, where I learned to blend critical thinking with interdisciplinary research—developing a mindset for tackling complex, real-world challenges.
At the University of Manchester, I took a deep dive into molecular biology research through an MRes in Tissue Engineering for Regenerative Medicine. There, I developed a gene therapy model for a genetic muscle-wasting disease, which acted as a proof-of-principle to support early stage clinical trials. During this time I strengthened my hypothesis-driven problem solving approach and my ability to leverage data to tell stories at the intersection of biomedical engineering and data analysis.
As a former science coordinator in the UAE public education system, I designed national exams, and later began integrating generative AI tools into the classroom. These experiences sparked my current focus of understanding data to help build AI systems that empower how people learn—ethically, adaptively, and with lasting impact.