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”}]