Zheng Liu
· FacultyUniversity of California, Santa Barbara · Mathematics
Active 1981–2026
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About
Zheng Liu is an associate professor at the University of California, Santa Barbara. He received his Ph.D. from Columbia University in 2016 under the supervision of Eric Urban. His research area is number theory, with a particular focus on p-adic properties of automorphic forms, special L-values, and Iwasawa theory. His work involves deep investigations into p-adic L-functions, theta lifts of Hida families, and the arithmetic of modular forms. Liu's research contributions include studies on derived p-adic heights, the leading coefficients of p-adic L-functions, and the Iwasawa Greenberg main conjecture for non-ordinary modular forms. His collaborations with other mathematicians have led to advances in understanding Eisenstein congruences, Archimedean zeta integrals for unitary groups, and the theory of Klingen Eisenstein series on symplectic groups. Overall, his research advances the understanding of the interplay between automorphic forms, p-adic analysis, and arithmetic geometry.
Research topics
- Computer Science
- Artificial Intelligence
- Data Mining
- Machine Learning
- Reliability engineering
- Engineering
- Natural resource economics
- Computer vision
- Ecology
- Environmental planning
Selected publications
Journal de l’École polytechnique — Mathématiques · 2026-05-22
articleOpen access1st authorCorrespondingWe construct a four-variable <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> -adic <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>L</mml:mi> </mml:math> -function for cuspidal Hida families on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi mathvariant="normal">GSp</mml:mi> <mml:mo>(</mml:mo> <mml:mn>4</mml:mn> <mml:mo>)</mml:mo> <mml:mo>×</mml:mo> <mml:mi mathvariant="normal">GL</mml:mi> <mml:mo>(</mml:mo>…
Radioengineering · 2025-08-07
articleOpen accessAccurate detection of mill conditions during the cement grinding process directly impacts the quality of particle size distribution and energy consumption per ton of cement. This paper proposes a mill condition classification method based on three-axis wireless vibration sensing and deep feature learning to address issues such as distortion of mill condition characterization caused by power grid disturbances in traditional electrical power methods and sound transmission attenuation in mill sound…
Recent grants
Frequent coauthors
- 200 shared
Huan Liu
- 130 shared
Tao Zha
Emory University
- 119 shared
Jian Ge
Southeast University
- 100 shared
Salvatore Baglio
University of Catania
- 100 shared
Shervin Shirmohammadi
University of Ottawa
- 99 shared
Alessandro Ferrero
- 98 shared
Vice Provost
University of Ottawa
- 98 shared
Reta Wehmeier
Argonne National Laboratory
Education
- 2007
Ph.D.
University of Ottawa
- 2000
Ph.D.
Kyoto University
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