Songwan's blog

Statistics graduate school life

About Me


Songwan Joun

Hello, I'm Songwan Joun. I am graduate student studying Statistics at University of Victoria, Canada. This blog is a place where I post my interests and ideas. My interests lies in Machine learning and Biostatistics. If you want to communicate with me, please feel free to contact me.


    CV: here      Github: songwan      Email: songwan.joun@gmail.com

Current projects


Big data & Biostatistics (current project, 2019)

To be added soon
manuscript      source code


Handling correlated genes (paper in progress, 2018)

Handling highly correlated genes of Single-Cell sequencing data in multiple regression models
manuscript      source code

Ideas


Robustifying clustering algorithm (2018)

Robustifying clustering algorithm by adapting robust covariance matrix on the initial stage of TCLUST algorithm
manuscript      source code


PM10 level visualization (2017)

RShiny, PM10 level visualization of my hometown Daegu for every bus stops
description      source code

Work Experience


Summer Research Assiatant

University of Victoria (May 2019 - Aug 2019)

Led simulation studies, compared machine learning models using cross-validdation


Junior Researcher

Holonyx (Sep 2017 - Mar 2018)

Visualized levels of PM10 in Daegu city and predicted PM10 levels


Part-time R Instructor

Kyungpook National University (Jul 2017 - Sep 2017)

Trained basic and intermediate R programming to university students


Intern researcher

Research Korea (Dec 2016 - Feb 2017)

Examined tables, plots, and context in survey reports and adjusted errors

Education


Master of Science, Statistics (Sep 2018 - Current)

University of Victoria BC, Canada

Supervised by Dr. Xuekui Zhang
VADA
Trainee Scholarship (NSERC CREATE) $16,000


Bachelor of Science, Statistics (2013 - 2017)

Kyungpook National University , Daegu, South Korea

Minor in Computer Science
Exchange term at Dalhousie University , Halifax, NS, Canada ( Sep 2015 - Apr 2016 )

Statistical Skills

• Took bioinformatics, survival analysis, robust, and ML courses

• Performance comparison of Neural Network and traditional Statistical methods by data size

• Handling highly correlated genes of Single-Cell sequencing data in multiple regression models

Programming Skills


R

Have a good understanding of R

Conducted simulation studies, applied statistical methods


Compute Canada

High performance computing system

Used Compute Canada to handle big data, batch and parallel jobs


Python

Basic knowledge in Python

Made digit classifier using CNN, Tensorflow


SAS

SAS Certified Base Programmer for SAS 9 (SAS)

Basic knowledge in SAS


IBM Data Scientist

Mastery Award for Students (IBM)

Took IBM Data Scientist Course

Hobbies

• Love Swimming

• Blogging

• Learning languages including programming languages!