Yuhai Tu


Yuhai Tu




IBM Research - Yorktown Heights Yorktown Heights, NY USA


Yuhai Tu graduated from University of Science and Technology of China in 1987. He came to the US under the CUSPEA program and received his PhD in physics from UCSD in 1991. He was a Division Prize Fellow at Caltech from 1991-1994. He joined IBM Watson Research Center as a Research Staff Member in 1994 and served as head of the theory group during 2003-2015. He has been an APS Fellow since 2004 and served as the APS Division of Biophysics (DBIO) Chair in 2017. He is also a Fellow of AAAS. 

For his work in theoretical statistical physics, he was awarded (together with John Toner and Tamas Vicsek) the 2020 Lars Onsager Prize from APS: 'For seminal work on the theory of flocking that marked the birth and contributed greatly to the development of the field of active matter.' https://www.aps.org/programs/honors/prizes/prizerecipient.cfm?last_nm=Tu&first_nm=Yuhai&year=2020

Yuhai Tu has a diverse range of research interests from Physics, Biology, Material Science, to Machine Learning. His PhD and Postdoc work were on nonlinear dynamics and pattern formation in nonequilibrium systems. After joining IBM Research in 1994, he did pioneering work on collective phenomena in active systems (flocking dynamics), surface physics (Si-SiO2 interface), and nonequilibrium phase transitions. Since 2000, his research interests shift to biological physics. He has made seminal contributions in many areas of biological physics including algorithm development and statistical analysis for high throughput transcriptome data (microarray analysis); quantitative modeling of signal transduction and motility in bacterial chemotaxis; and thermodynamics of nonequilibrium biochemical networks. His recent work focuses on three directions: (1) dynamics of biological networks -- biochemical networks for signal transduction and neural networks for coding and computation; (2) thermodynamics of information processing in biological systems; (3) statistical physics of learning in brain and in artificial neural networks. His full publication list can be found in Google Scholar: [https://scholar.google.com/citations?hl=en&user=bpaBVYIAAAAJ&view_op=list_works] (https://scholar.google.com/citations?hl=en&user=bpaBVYIAAAAJ&view_op=list_works)



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