Jongsu Kim

Machine Learning Research Engineer

Email: jongsukim8@gmail.com

Phone: +82 10-2019-8869

Web: liam.kim

About Me

Hi, my name is Jongsu Kim, I’m a upcoming PhD qualified by a research background in machine learning and mathematical modeling focused on time series forecasting and computational fluid dynamics.

I have a strong coding ability both in producing clean and efficient code. Moreover, with mathematically modeling experience, I have strong analytic skills. I also enjoy learning and mastering new technologies.

SKILLS (WIP)

Machine Learning and Deep Learning

Time Series forecasting, Natural Language Processing

Mathematical Modeling

Statistics, Computational Fluid Dynamics, Numerical Analysis

Languages

Python, Julia, C++, Fortran, MATLAB, HTML/CSS, TypeScript

Frameworks

PyTorch, Tensorflow, Keras, Flux.jl

Code and Code Quality Managing

Git, GitHub, Travis-Ci, Github Actions, pytest, tox

Server Engineering

Linux, High Performance Computing, Cloud Computing (AWS, GCP)

EXPERIENCE (WIP)

Yonsei University

Computational Science and Engineering

09/2011 ~ Current

SK C&C

Full time work

07/2010 ~ 08/2010

I learned Database management using C# and SQL.

EDUCATION (WIP)

Yonsei University, South Korea

PhD Computational Science and Engineering

09/2011 ~ Current

Expected defense data: Jun. 2021

Yonsei University, South Korea

BSc Atmospheric Science, BSE Computer Science

03/2007 ~ 08/2011

PUBLICATION

  • Gihun Shim, Jongsu Kim, and Changhoon Lee. Path instability of a spheroidal bubble in isotropic turbulence, Physical Review Fludis, Submitted
  • Particulate matter (PM) forecasting using machine learning method, Jongsu Kim, Changhoon Lee, in manuscript

Awards

[{“layout”=>”top-middle”, “title”=>”NVIDIA CUDAtm Coding Contest”, “sub_title”=>”BSc Atmospheric Science, BSE Computer Science\n”, “caption”=>”03/2010”, “description”=>”Designated Subject: Matrix Multiplication\n”}]

Open Source Contributions (WIP)