Speaker: Seyoon Ko, Ph.D.
IDRE Fellow and Assistant Adjunct Professor,
Mathematics Department,
University of California Los Angeles

Location: Virtual
Link to the recording: https://youtu.be/lmtHtuyl-Q0 

Abstract: Julia (http://julialang.org) is a modern open-source programming language for technical computing. Its design offers much greater speed and productivity compared to R or Python, as high-performance code does not need to be wrapped in a low-level language like C or Fortran. After almost a decade of active development, Julia reached its first major release, v1.0, in 2018, and is quickly gaining popularity in scientific computing and data science communities. In this workshop, I will present the basic concepts of Julia and show a little comparison between Julia and other languages, such as R, C, and Python.

About the speaker: Dr. Ko is an Assistant Adjunct Professor at UCLA Mathematics. Previously, he was a Postdoctoral Scholar working with Dr. Ken Lange and Dr. Hua Zhou in the Department of Computational Medicine. Dr. Ko’s research interests include large-scale computational methods in biostatistics and bioinformatics using parallel and distributed computing. He earned a Ph.D. degree in Statistics from Seoul National University in South Korea, as well as a M.S. degree in Computational Sciences and a B.S. degree in Physics, Mathematical Sciences, and Computational Science.