Prof. Xin Liu received her B.S. in Physics from Tsinghua University in 2004 and her Ph.D in Astrophysical Sciences from Princeton University in 2010 under the guidance of Prof. Michael A. Strauss. Before joining UIUC in 2015, she was a NASA Einstein Fellow at Harvard and a Hubble Fellow at UCLA. 

Astronomical survey and data science

Multi-messenger and time-domain astrophysics

AI for science

Astronomy has always been driven by data. Yet only in recent years has it truly become a big data field. With automatic surveys recording the sky at unprecedented speed, the sheer volume of astronomical data introduces new challenges and opportunities. Modern Astronomy pushes the boundaries of data analysis and artificial intelligence, providing a great domain for machine learning (ML) research. The discipline is entering a phase of maturation, progressing beyond the simplistic utilization of pre-packaged, opaque ML models and evolving towards methodologies where ML plays an essential role within a broader, principled analysis framework. Our current research is focused on three evolving domains where the intersection of ML and astronomy forms symbiosis: (1) Physics-informed learning, (2) Statistical learning with probabilistic frameworks, offering capabilities such as uncertainty quantification and generative models, and (3) Transparent and interpretable ML models for scientific analyses, emphasizing robustness, accuracy, and comprehensibility.

Ph.D. in Astrophysical Sciences, Princeton University, 2010
B.S. in Physics, Tsinghua University, 2004

Norman P. Jones Professorial Scholar, 2023-2026

Excellent Teacher Ranked by Students, 2023

NCSA Faculty Fellow, 2020 & 2023

ASTR 596 - AI and Big Data in Astronomy
ASTR 350 - The Big Bang, Black Holes, and the End of the Universe
ASTR 330 - Extraterrestrial Life

210 Astronomy
1002 W. Green St.
Urbana, IL

(217) 265-8073