MD Mehedi Hasan

I'm Mehedi, a final-year Computer Science student from Bangladesh who builds software systems and explores the world through code, research, and travel. What drives me is understanding how things work—whether that's a neural network processing language, a distributed system handling millions of requests, or the historical forces that shaped modern societies.

I believe the best engineers are curious about more than just technology. They understand context, see patterns across disciplines, and build solutions that matter to real people. That perspective shapes everything I do, from writing production code to researching low-resource language processing.

Technical Journey

My engineering journey started with a simple question: how do you build something that actually works at scale? That curiosity led me to full-stack development, where I've worked with Next.js, Django, Node.js, and FastAPI to build systems that handle real users and real data.

I've built RAG pipelines that make AI systems more useful, chat interfaces that feel natural, and automation platforms that save time. Each project taught me something new about system design, data flow, and the importance of thinking through edge cases before they become problems.

What I enjoy most is taking complex ideas and making them accessible. I explain neural networks using everyday analogies, break down system architectures into digestible pieces, and write code that tells a clear story. Clarity isn't just nice to have—it's what separates good engineering from great engineering.

Research and Learning

My research interests center on making AI more inclusive and useful for everyone, especially speakers of low-resource languages. I work on natural language processing, speech processing, and using large language models to generate synthetic data that helps bridge gaps in training datasets.

I've built prediction models, experimented with transformer architectures, and analyzed data to find patterns that weren't obvious at first glance. Machine learning, for me, is about understanding the underlying mathematics while staying grounded in practical applications.

The most exciting problems are the ones where technology meets real-world constraints. How do you build a model that works well when you don't have millions of labeled examples? How do you design a system that's both powerful and efficient? These questions keep me learning and experimenting.

Beyond Technology

My curiosity extends well beyond code. I'm fascinated by history—how ancient civilizations built systems that lasted centuries, how medieval empires managed complexity without modern tools, and how modern events shape the world we live in today. Understanding the past helps me see patterns in how societies organize, communicate, and solve problems.

Geography and travel give me a different lens on the same questions. When I explore new places, I'm not just seeing sights—I'm observing how different cultures approach similar challenges, how geography influences development, and how people build communities in diverse environments.

These interests aren't separate from my technical work. They inform how I think about user needs, system design, and the impact of technology on communities. The best products understand their users' context, and context comes from understanding people, places, and history.

Current Focus and Future

Right now, I'm focused on growing as a full-stack engineer with strong system design skills. I want to build AI-driven products that solve real problems, not just demonstrate technical capability. That means understanding users deeply, designing for scale from the start, and iterating based on feedback.

I'm also continuing my research in NLP and low-resource languages, exploring how we can make AI systems more accessible to speakers of languages that don't have massive training datasets. This work matters because technology should serve everyone, not just those who speak dominant languages.

My long-term vision is to use technology to understand and positively impact people, cultures, and communities globally. That might mean building products that help people communicate across language barriers, creating tools that make knowledge more accessible, or contributing to research that makes AI more inclusive. The path isn't fully mapped, but the direction is clear: build things that matter, for people who need them.

If you're working on interesting problems in software engineering, AI, or research, or if you share similar interests in technology and world exploration, I'd love to connect. Let's build something meaningful together.