Available for opportunities
Aspiring Machine Learning Engineer
Building intelligent systems that transform raw data into real-world decisions — with a focus on healthcare, education, and the problems that matter most.
IT & Health Informatics student with a machine learning mindset.
I'm an Information Technology and Health Informatics student with a deep interest in how data and intelligent systems can transform the way we make decisions — especially in spaces where those decisions affect people's lives.
Over the past year, I've been building hands-on experience through real projects: from machine learning recommendation systems to web applications designed around student success. Each project taught me something new about what it means to take data from raw noise to meaningful output.
My technical foundation spans Python, Pandas, Scikit-learn, SQL, Flutter, and Firebase — and I'm constantly adding to that toolkit. I believe good engineering isn't just about writing code; it's about understanding the problem deeply enough to solve it elegantly.
I'm particularly driven by the intersection of healthcare and technology — a space where better data pipelines and smarter models could mean earlier diagnoses, more equitable access to care, and better outcomes for millions of people.
I'm always open to learning, collaboration, and contributing to work that matters.
A machine learning recommendation engine that suggests films based on content similarity algorithms, complete with live movie poster retrieval and model evaluation — turning raw preference data into a personalized viewing experience.
A web application designed to help students take ownership of their academic journey by tracking attendance, logging study hours, and monitoring performance in one unified dashboard. Built to make academic data visible and actionable.
Began studying Information Technology and Health Informatics, building core programming skills in Python and exploring how data flows through real systems.
Moved into hands-on machine learning — learning Pandas, Scikit-learn, and model development. Applied these tools to real datasets and built my first recommendation system.
Expanded into software development with Flutter, Firebase, and Flask; building end-to-end applications that tie data science outputs to real user experiences.
Continuing to deepen expertise in ML engineering, exploring AWS, and looking for opportunities to contribute to meaningful technology projects.
I believe the most powerful technology is technology that serves people who need it most. My interest in Health Informatics isn't academic — it's personal. I want to build ML systems that support earlier diagnosis, help clinicians make better decisions, and give communities access to insights that have historically been locked behind expensive expertise.
In education too, I see a massive opportunity. Tools like Academic Companion are a small start, but I'm driven by the bigger question: how can intelligent systems help more students succeed, regardless of their background?
My goal is clear: to become a professional Machine Learning Engineer working on systems that have a tangible, positive impact in the real world. I want to work at the intersection of rigorous data science and practical software — building models that don't just perform well on paper but actually ship, scale, and serve people.
In the near term, I'm focused on deepening my ML foundations, gaining industry experience through internships and collaborative projects, and contributing to open-source work in healthcare or education technology.
Whether you're a recruiter looking for a driven ML engineer candidate, a developer who wants to collaborate, or just someone curious about my work — I'd love to hear from you. Let's build something meaningful together.
I'm actively looking for internships, collaborative projects, and entry-level ML engineering roles. If you're building something that matters, let's talk.