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Abs:

Generative AI is rapidly evolving from a simple question-answering tool into a working environment that supports code generation, execution, document editing, and automation. This talk introduces how researchers can use vibe coding to turn ideas into code and concrete outputs. It briefly reviews recent AI tools such as ChatGPT, Claude, Gemini, Cursor, and Claude Code, and discusses practical ways to use AI for Python, R, LaTeX, data analysis, visualization, and research writing. The goal of this talk is to provide a starting point for researchers to understand AI-assisted workflows and adopt them in ways that fit their own work.

 

Bio: 

Guebin Choi is an Associate Professor in the Department of Statistics at Jeonbuk National University, where he also serves as Director of the Applied Statistics Research Institute. He received his Ph.D. in Statistics from Seoul National University in 2018. Before joining Jeonbuk National University, he worked at the Artificial Intelligence Research Institute of LG Electronics. His research focuses on multiscale methods for representing and analyzing data across multiple levels and scales. His recent work develops multiscale approaches for non-Euclidean data structures, including graphs, manifolds, and simplicial complexes, with connections to geometric deep learning and topological deep learning.