Dr. Haiyan Liu

Dr. Haiyan Liu

Profile

I am an associate professor in the School of Mathematics at the University of Leeds. My research focuses on functional, longitudinal, and time series data. I joined the University of Leeds in 2016 as a (Turing) research fellow under the supervision of Prof. Jeanine Houwing-Duistermaat, became a University Academic Fellow in 2019, and was promoted in 2025. I completed my PhD in statistics under the supervision of Prof. Jan Beran at the University of Konstanz in 2016.

Research interests

I have primarily worked on first-generation functional data, which involves scalar observations recorded over a continuum, such as time. My works are mainly on functional principal component analysis under dependent errors or with informative missingness, functional regression models, and functional clustering models. More recently, I have become interested in second-generation functional data, which extends to more complex objects, such as brain images, traffic networks.

Research groups and institutes

  • Statistics

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>
Projects
    <li><a href="//phd.leeds.ac.uk/project/2021-functional-data-analysis-models-for-count-data">Functional data analysis models for count data</a></li> <li><a href="//phd.leeds.ac.uk/project/2395-functional-data-analysis-with-informative-missingness">Functional data analysis with informative missingness</a></li> <li><a href="//phd.leeds.ac.uk/project/2410-functional-data-analysis-with-informative-missingness-(uk-only)">Functional data analysis with informative missingness (UK Only)</a></li> <li><a href="//phd.leeds.ac.uk/project/2128-functional-regression-models-with-application-in-neuroimaging-data-analysis">Functional regression models with application in neuroimaging data analysis</a></li> <li><a href="//phd.leeds.ac.uk/project/2153-novel-methods-for-high-dimensional-output-analysis-for-agent-based-models">Novel Methods for High-Dimensional Output Analysis for Agent-Based Models</a></li>