Engineering the Future of Artificial Intelligence: Stanford Fellows Backed by Amazon

Ten Stanford University PhD candidates were recently selected for the Amazon AI PhD Fellowship, a program that funds emerging researchers tackling some of the most difficult challenges in the field. These scholars will receive two years of funding and Amazon Web Services credits to support their research in diverse areas such as deep learning, genetics, and statistics. This initiative, which supports over 100 students across multiple universities, aims to bridge the gap between academic theory and practical, useful AI applications.

Among the recipients, Ken Ziyu Liu is developing a privacy layer for large language models called the Open Anonymity Project. His research focuses on creating a system that functions like a virtual private network, allowing users to interact with AI without revealing their identities to the service providers. This approach keeps personal history stored locally on the user device instead of on corporate servers, giving individuals total control over their digital memory.

In the field of genetics, Valeh Valiollah Pour Amiri is designing what she calls a glass box AI model to simulate cellular functions. Her work seeks to replace black box systems with interpretable architectures that mirror biological processes like DNA binding and chemical modifications. This mechanistic virtual cell could eventually allow researchers to test new drug hypotheses digitally before starting expensive clinical trials, pinpointing exact molecular changes affected by genetic modifications.

Statistics student Noah Cowan is applying mathematical approaches to improve brain-computer interfaces for paralyzed individuals who are unable to speak. His research addresses the problem of shifting brain signals, which often makes these communication tools less accurate over time. By building models that consider multiple possibilities of what a user intended to say, he hopes to create a smoother and more reliable experience with less friction for patients.

The complete cohort of selected Stanford fellows includes Mohammad Asadi, Noah Cowan, Michelle Ho, Yingxi Li, Liam O'Carroll, Rishabh Ranjan, Chenglei Si, Tristan Thrush, Valeh Valiollah Pour Amiri, and Ken Ziyu Liu. Their collective efforts represent the next generation of scientific leadership across aeronautics, natural language processing, and statistical modeling. More information about the program and the work of these Stanford AI fellows is available through the Stanford Institute for Human-Centered AI.