・Title: Statistical Distances with Mathematical Explanation
Speaker: Prof. GIM Minjung
      National Institute for Mathematical Sciences/
      Ajou University Department of Mathematics, Korea

・Title: Statistical Learning Models in Functional structure of Clinical data
Speaker: Prof. Soon-Sun Kwon
      Ajou University Department of Mathematics, Korea

・Place: IMI Auditorium(W1-D-413) and Live streaming with zoom
Attendance: 50 (Students: 40; Staff: 10)

At the colloquium in July, we had two speakers, Prof. GIM from the National
Institute of Mathematical Sciences, Korea, and Prof. Kwon from Ajou University.

Prof. GIM introduced statistical distance, which is used in various machine
learning applications to measure the distribution of data and the differences
among samples. He also introduced several commonly used statistical distance
functions implemented in SciPy, and explained their operating principles and
properties with visual explanations. In addition, he showed examples of
application to actual examples. This enabled us to understand the
usefulness of each statistical distance introduced.

Prof. Kwon first introduced a case study in which he applied his proposed
clustering method using Frechet distance for multidimensional functional data to
multidimensional thyroid cancer data collected in Korea. Then, he introduced the
multivariate analysis method to investigate the relationship between
kinematic gait measurements and GMFCS levels based on gait data from both normal
and cerebral palsy (CP) patient groups with various Gross Motor Function
Classification System (GMFCS) levels. He also showed that the proposed method
enables prediction with good accuracy and provides discriminant functions with
easy interpretation.