Jialin Liu

Jialin Liu is an Assistant Professor in the Department of Statistics and Data Science at the University of Central Florida (UCF) and a member of the UCF AI Initiative. His academic background includes a B.S. in Automation from Tsinghua University (2015) and a Ph.D. in Applied Mathematics from UCLA (2020).

• Education:
  • B.S. in Automation, Tsinghua University (2015)
  • Ph.D. in Applied Mathematics, University of California, Los Angeles (2020)

Liu's research bridges AI, data science, and mathematics. He focuses on developing AI/data-driven methodologies to address computational mathematical problems such as optimization, differential equations, and numerical linear algebra. His work emphasizes the need for stable, safe, and explainable data-driven methods while establishing rigorous theoretical foundations for integrating AI into mathematics and science.

The 15 most recent publications highlight interdisciplinary advancements in areas like matrix completion, graph neural networks for optimization, sparse coding for phase restoration, and theoretical frameworks for learning-to-optimize. These works span algorithm design, mathematical foundations of AI, and applications in computational mathematics.