Hao Yan

Hao Yan is a Chinese-American chemist, a (bio)molecular designer, programmer and engineer.

Hao Yan graduated from Shandong University, and completed doctoral study in the subject of DNA nanotechnology at New York University, under the direction of Nadrian Seeman in 2001. Yan began his career as an assistant research professor at Duke University, before assuming an assistant professorship at Arizona State University in 2004. He was directly promoted to full professor with early tenure in 2008. In 2012, Yan was named ASU's first Milton D. Glick Distinguished Chair of Chemistry and Biochemistry. The next year, Yan became director of ASU's Center for Molecular Design and Biomimetics. In 2018–2022, Yan was ranked as a highly cited researcher by Web of Science,. He was an elected fellow of the American Association for the Advancement of Science., the National Academy of Inventors and the American Institute for Medical and Biological Engineering. Yan received the 2020 Feynman Prize in Nanotechnology for the experimental category, and the Rozenberg Tulip Award in DNA Computing in 2013. Other honors for Yan include: Humboldt Research Award (2023), Fast Company's 100 Most Creative People in Business (2019), Alfred P. Sloan Research Fellowship (2008), National Science Foundation CAREER Award (2006-2011), Air Force Office of Scientific Research Young Investigator Award (2007-2010), the Arizona Technology Enterprise Innovator of Tomorrow Award (2006), and the Arizona Technology Enterprise Achievement Award (2014).

The theme of Yan's research is to use nature's design rules as inspiration to advance biomedical, energy-related, and other technological innovations through the use of self-assembling molecules and materials. The objective is to create intelligent materials with better component controls at the atomic and molecular levels. Yan's interdisciplinary team is interested in designing bio-inspired molecular building blocks such as DNA, RNA and proteins and programming their higher order assembly into systems that will perform complex functions. The ultimate goals are 1) to engineer an information guided self-assembling molecular system for the finest possible interactions of molecules in a three-dimensional space; and 2) to create man-made molecular machines/molecular robotics through molecular design, molecular programming, directed molecular evolution and molecular systems engineering.