About

Jeongwhan Choi is an integrated Ph.D. student in the Department of Artificial Intelligence at Yonsei University. He has a broad interest in graph neural networks, recommender systems, spatio-temporal forecasting, and differential equations. Jeongwhan is currently working on developing graph-based deep learning methods inspired by differential equations in natural science, specifically diffusion equations. Jeongwhan completed his undergraduate studies in Software Engineering at Jeonbuk National University, where he was advised by Prof. Suntae Kim and Prof. Duksan Ryu. During his undergraduate studies, he was involved in several research projects related to software engineering, such as cross-project defect prediction, configuration bug reports, and automated parameter optimization. He also worked on a project related to the development of a capability assessment evaluation algorithm for personalized self-study with Hanja-Chinese parallel. Jeongwhan's research interests include graph neural networks, spatiotemporal forecasting, neural ODEs/CDEs/RDEs, recommender systems, software engineering, and software defect prediction. He has a total relevant experience of 2.86 years and has worked as a research scientist on neural networks, AI, deep learning, big data, and ML. Jeongwhan has a combined MS/PhD degree in Artificial Intelligence from Yonsei University. He also holds nanodegrees in Self-Driving Car Engineering and Machine Learning from Udacity and a Machine Learning certificate from Coursera. He completed a course on IBM Blockchain Foundation for Developers from Coursera as well.