About

I'm an undergraduate student at Duke University (Class of 2027), majoring in Physics and Mathematics. My current work sits at the intersection of deep learning, scientific imaging, and quantum information. At the Center for Virtual Imaging Trials, I work on deep learning for 3D CT data: training U-Net style architectures for multi-organ segmentation, building registration pipelines for anatomical alignment, and developing conditional diffusion models over signed-distance function volumes to generate realistic organ geometries. I enjoy thinking about how model architecture, inductive biases, and physics constraints interact in these systems. In parallel, I'm studying quantum information and symmetric quantum circuits through coursework and an independent study with Prof. Iman Marvian, where I explore energy-conserving and permutation-symmetric unitaries and how group and Lie-algebra structure constrains quantum circuit families. I grew up in Nepal, and I care a lot about accessibility to education and scientific opportunities for students from under-resourced backgrounds. I've mentored high school students in Nepal on quantum algorithms and Olympiad preparation, and I hope to keep building bridges between research, technology, and communities like the one I come from. Outside of academics, I like chess, cooking, and the occasional long ranty blog post about learning and uncertainty.