I am an AI scientist, with a background in Statistics and Information Theory, specializing in Gen AI, recommender systems, and privacy-preserving methods. My work bridges theoretical research—in areas such as statistical learning theory, high-dimensional probability, and information theory—with applied system design for enterprise-scale products and data collaboration platforms.

I have designed and deployed machine learning systems that support large-scale, production-level applications, and my research has been published in leading venues including NeurIPS, ICML, ICLR, UAI, and IEEE Transactions. I currently serve as an Applied Scientist at Amazon AWS, where I drive the development of next-generation AI technologies, and previously worked as a Research Scientist at Meta.

Beyond research, I bring experience in leading research-to-production pipelines, mentoring scientists, and delivering measurable impact across teams and organizations. I am also a PhD candidate at Caltech (on leave) and hold a Master’s degree in Electrical Engineering from Arizona State University and a Bachelor’s degree from Sharif University of Technology.