Jongsu Kim

• Focused on multifaceted problem-solving to address diverse and complex challenges across various topics
• Refined LLM training data and reduced training costs through a data-centric approach
• Controlled false alarms by implementing anomaly detection tailored for digital transformation using limited factory equipment and vibration data
• Managed a project to enhance the performance of unsupervised learning vision inspection models for detecting new defects
• Improved system stability by leveraging AWS metrics for data-driven anomaly detection and false alarm control
• Developed and deployed an end-to-end anomaly detection solution in a production environment

• 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)

Related course work

• 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)

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