Office of Engineering Communications
Computer scientists Tri Dao and Ellen Zhong have been named AI2050 Early Career Fellows by Schmidt Sciences.
The AI2050 fellowships fund researchers who are working to solve hard problems in AI and improve technology for the benefit of humanity by 2050. Dao and Zhong are two out of 21 early career fellows who will receive funding over the next three years.
Schmidt Sciences, founded by Eric and Wendy Schmidt, provides funding to support and accelerate scientific research. Eric Schmidt studied electrical engineering at Princeton before going on to become the CEO and executive chairman of Google. In a press release, Schmidt said that “AI is underhyped, especially when it comes to its potential to benefit humanity. The AI2050 fellowship was established to turn that potential into reality—by supporting the people and ideas shaping a healthier, more resilient and more secure world.”
Dao, an assistant professor, works at the intersection of machine learning and systems. His research focuses on designing hardware-aware algorithms to improve the efficiency of machine learning systems. Recent work has contributed to improving the design and architecture of transformers in machine learning, a key step to creating more accurate and efficient large language models. His project as an AI2050 fellow will focus on developing intelligent systems that can learn through experimentation, an advance that could enable AI to discover new solutions in domains where human experts are scarce, like advanced engineering and scientific research.
Dao joined the Princeton faculty in 2024 after completing doctoral and bachelor degrees at Stanford University. He is the co-founder and Chief Scientist of TogetherAI. He has been named a Google Research Scholar and received a junior faculty award from Google ML and Systems.
Zhong, an assistant professor, is an expert in computational biology. Her research focuses on the direct observation of proteins and molecules at the atomic level through cryo-electron microscopy (cryo-EM) and tomography (cryo-ET). Her work as an AI2050 fellow will develop new AI tools to integrate cryo-EM and cryo-ET imaging data with protein structure prediction models. Zhong’s work allows researchers to create high-resolution 3D visualizations of proteins and other biomolecules directly within cells, improving both the accuracy and efficiency of biomolecular structure determination. These advances will deepen our understanding of how proteins operate at the atomic level and may lead to new discoveries about the molecular mechanisms underlying health and disease.
Zhong joined the Princeton faculty in 2022 after completing her doctoral work at MIT. Her work has been recognized by a E. Lawrence Keyes, Jr./Emerson Electric Co. Faculty Advancement Award and a commendation for outstanding teaching, both from Princeton’s School of Engineering and Applied Science. She received a bachelor of science degree from the University of Virginia.