Dr Haeran Cho
BSc, PhD
Expertise
Research interests include data segmentation (a.k.a. change point analysis), time series analysis and high dimensional statistics.
Current positions
Associate Professor in Statistics
School of Mathematics
Contact
Press and media
Many of our academics speak to the media as experts in their field of research. If you are a journalist, please contact the University’s Media and PR Team:
Projects and supervisions
Research projects
Statistical Foundations for Detecting Anomalous Structure in Stream Settings DASS
Principal Investigator
Managing organisational unit
School of MathematicsDates
01/09/2024 to 31/08/2029
Quantile factor modelling for high-dimensional time series
Principal Investigator
Description
Time series data (observations indexed by time or other meaningful orderings) are encountered in many areas such as finance, economics, medicine, engineering, natural and social sciences. A recent challenge which…Managing organisational unit
Dates
22/01/2019 to 08/07/2019
Quantile factor modelling for high-dimensional time series
Principal Investigator
Description
Time series data (observations indexed by time or other meaningful orderings) are encountered in many areas such as finance, economics, medicine, engineering, natural and social sciences. A recent challenge which…Managing organisational unit
Dates
03/01/2019 to 31/07/2019
Change-point detection for high-dimensional time series with nonstationarities
Principal Investigator
Managing organisational unit
School of MathematicsDates
25/06/2016 to 24/12/2017
Thesis supervisions
Publications
Recent publications
17/03/2025Nonparametric data segmentation in multivariate time series via joint characteristic functions
Biometrika
Data segmentation algorithms
Econometrics and Statistics
FNETS
Journal of business & economic statistics
High-dimensional data segmentation in regression settings permitting temporal dependence and non-Gaussianity
Electronic Journal of Statistics
High-Dimensional Time Series Segmentation via Factor-Adjusted Vector Autoregressive Modeling
Journal of the American Statistical Association