Jongsu Kim

Machine Learning Researcher


Phone: +82 10-obfuscate2019-obfuscate8869


About Me

Hi, I’m Jongsu Kim. I’m a Ph.D. in Computational Science and Engineering-Mechanical/Electrical Engineering qualified by a research background in machine learning and mathematical modeling focused on time series forecasting and computational fluid dynamics.

I can do mathematical or physical modeling numerically and have analytic skills for physical phenomenon. Not only modeling skills, I also have a strong computer science background and like to actively learn new technologies.


Machine Learning and Deep Learning

Time Series Forecasting, Natural Language Processing

Machine Learning Frameworks

PyTorch, Tensorflow, Keras, Flux.jl

Programming Languages

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


Numerical Analysis, Statistics, Partial Differential Equation

Fluid Mechanics

Computational Fluid Dynamics, Turbulence Modeling, Immersed Boundary Method

Code and Code Quality Managing

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

Server Engineering

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


Artifical Intelligence Professional


10/2021 ~ Present

  • AI Researcher

Ph.D. Student

School of Mathematical Computing, Yonsei University, South Korea

09/2011 ~ 08/2021

  • Particulate Matter (PM) forecasting by deep learning methods for time series forecasting (2018-2021)
  • Modeling and simulation of finite-size particles in homogeneous isotropic turbulence using psuedo-spectral methods and immersed boundary methods (2015-2018)
  • Modeling and simulation of finite-size droplets in laminar flows with gravity field using level set methods (2011-2015)
  • Communicate to support laboratory colleagues who was struggling with computer science-related problems such as algorithms, debugging, and so on. The process was then documented so that the next time the team encountered the same situation, they could follow a similar procedure.
  • Programming knowledge (mainly Julia, C++, Fortran)
  • Create web pages for multiple purposes in the department, such as conference, introduction pages, and so on.
  • Administrator of laboratory server (cluster with ~30 nodes)


Yonsei University, South Korea

Ph.D. in Computational Science and Engineering-Mechanical/Electrical Engineering

09/2011 ~ 08/2021

  • Advanced Partial Differential Equations (PDE)
  • Advanced Numerical Analysis
  • Fluid Mechanics: Incompressible viscous flow and turbulent flow
  • Advanced CFD methods: Immersed Boundary Methods (IB Methods), Large Eddy Simulation (LES), Advanced projection method, Simulation using OpenFOAM
  • Cloud dynamics and atmospheric dynamics (lectures in Atmospheric Science)
  • Computational photography (lecture in Computer Science)
  • Multicore parallel programming (lecture in Electrical and Electronic Engineering)

Yonsei University, South Korea

BSc in Atmospheric Science, BSE in Computer Science

03/2007 ~ 08/2011

  • Undergraduate knowledge of Atomspheric Science
  • Undergraduate knowledge of Computer Science
  • National Science & Technology Scholarship (2007~2009)



  • Jongsu Kim and Changhoon Lee, 머신러닝 기반의 미세먼지 장기 예측 모델 개발, 2019, 대한기계학회 2019년도 추계학술대회
  • Jongsu Kim and Changhoon Lee, Predicting Concentration of Atmospheric Aerosol Particle using Machine Learning Technique, 2019, 2019년 한국계산과학공학회 춘계학술대회 및 정기총회
  • Jongsu Kim and Changhoon Lee, The numerical investigation on collision between two droplets within effects of gravity force, 2014, 제8회 유체공학 학술대회
  • Jongsu Kim and Changhoon Lee, 중력장 내에서의 두 액적 충돌에 관한 수치 시뮬레이션에 관한 연구, 2014, 대한기계학회 2014년도 추계학술대회
  • Jongsu Kim and Changhoon Lee, 중력 하에서의 액적 충돌 시뮬레이션, 2012, 대한기계학회 2012년도 추계학술대회


  • English (Intermediate, TOEIC 875, OPIc IH(Intermediate High))
  • Korean (Native)