Working on Computer Vision and Representation Learning.
I am an ML Research Engineer at CamCom Technologies, where I develop computer vision systems that bridge advances in machine learning research with real-world deployment. My work focuses on 3D vision, scene understanding, vision foundation models, representation learning, and training-free adaptation methods that enable large pretrained models to solve new tasks through in-context learning rather than additional optimization. I hold master's degrees in Computer Science and Mathematics, and my mathematical background continues to shape how I approach machine learning research, emphasizing first principles, geometric reasoning, and rigorous analysis. I am particularly interested in understanding how rich visual representations can be leveraged to build robust and scalable perception systems for challenging industrial applications. This website collects my research, technical writing, curated reading notes, and explorations across computer vision, representation learning, and mathematics. Beyond my research, I remain a hobbyist mathematician with a longstanding interest in number theory, drawn to the elegance of its ideas and the joy of exploring problems for their own sake.