About Me
Engineer, Researcher, AI enthusiast, and Lifelong learner.
I'm a software engineer with a strong foundation in computer science and a deep passion for machine learning, deep learning, and AI. My work ranges from building full-stack web apps to developing sophisticated deep learning models for applications like medical image analysis and crop classification.
I focus on combining good engineering practices with the latest AI techniques. I've tackled projects from brain tumor detection systems hitting 95% accuracy to complete student management platforms. I build software that works well and actually helps people.
Outside of coding, I'm usually experimenting with new ML approaches, contributing to open-source projects, or diving into my latest research.
Engineering Values
The principles that guide how I approach building software.
Simplicity First
Complex problems don't require complex solutions. I prioritize readability and maintainability over clever abstractions.
Measure Impact
Every feature should have a clear purpose. I focus on outcomes—reduced latency, improved user engagement, fewer bugs.
Own the Problem
I don't just implement tickets. I understand the context, question assumptions, and propose better solutions when I see them.
Continuous Learning
Technology evolves quickly. I stay curious, experiment with new tools, and share knowledge with my team.
Technical Skills
Technologies I use to bring ideas to life.
Languages
Frameworks & Libraries
Databases
Tools & Platforms
Beyond the Code
When I step away from the keyboard, you'll find me exploring new coffee shops, reading about system design and distributed systems, or hiking through local trails. I believe that creativity in engineering comes from having diverse experiences and staying curious about the world around us.
I'm always open to connecting with fellow engineers, discussing interesting technical challenges, or exploring potential collaborations. Feel free to reach out—I'd love to hear from you.