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Yuehua Wu (Amy)

Yuehua Wu (Amy)

Picture of Yuehua Wu (Amy)
Yuehua Wu (Amy)
Full Professor


Mathematics and Statistics


Office Location DB 2036
Phone Number (416) 736-5250 or (416) 736-2100 ext. 30109

Research Spotlight

Professor Yuehua (Amy) Wu (Mathematics & Statistics) is a researcher who considers interesting statistical problems with her students and models data to come up with analytical tools others can use.

“With statistics, you have to apply,” said Wu. “I train my students to have a good experience with data. We use real data and ask, what is it telling us? We come up with a model with theoretical results.”

One of Wu’s major research interests is change-point analysis. A changing point occurs when there is an abrupt change in the data, where the mechanism of what occurs before and after that point is different. Detecting and analyzing change points can be useful in many different application areas such as tracking stock markets, monitoring medical conditions, detecting climate change, monitoring and assessing the efficacy of the government policies, and more.

“Think of changing point in the context of having a security camera set up around your home,” explained Wu. “One can use changing point analysis to program their system to remove useless footage captures like the movement of squirrels or other animals, and keep more interesting footage of bigger things like people and cars.”

Throughout the COVID-19 pandemic, Wu has continued to work with collaborators virtually and is preparing numerous research papers for publication. Her recent research has focused on applying changing point analysis to medical imaging. She and her students have developed statistical methods to detect significant changes in images of gastrointestinal bleeds that can also be applied to detect injured lungs. Her methods try to detect meaningful differences in image pixels that indicate abnormalities, which could then be used to automatically alert doctors. The same tools could also be used in other applications such as for quality control, detecting smoke and pollution, and more.

“The idea is for these methods to be packaged as software that can be used by anyone,” added Wu. “People don’t have to fully understand the statistics behind them, they could just go into the software, input their data, and get results automatically.”

Research Interests

  • M-estimation
  • Model selection
  • Multiple change-point analysis
  • Multivariate analysis
  • Spatio-temporal modeling
  • High-dimensional statistics
  • Financial econometrics
  • Data mining
  • Missing data
  • Computational algorithms

Research Areas