I'm a Computer Science graduate with a strong passion for building intelligent, efficient, and impactful software. My work spans computer vision, natural language processing, and full-stack development — often blending machine learning with clean, accessible user interfaces.
I’ve led projects in AI-powered note summarization, voice-based assistants, and medical image translation using deep learning. My thesis focused on designing a lightweight worm-tracking system that analyzes posture using skeleton-based vision — an experience that sharpened my research, problem-solving, and data analysis skills.
I love working on tools that solve real-world problems, and I’m constantly exploring new technologies to improve both functionality and user experience.
Vision-based system for tracking posture and motion in microscopic worms using skeleton analysis.
Unpaired image-to-image translation model to generate MRI from CT scans using CycleGAN.
Neural network trained to predict depression levels in remote workers.
Offline voice assistant that uses Whisper and a transformer to classify intent and run tasks privately.
