I’m Jeongun Ha, a Ph.D. candidate in AIML-K. I majored in Representation Theory in the pure mathematics, but now I’m studying Generative Model and Neural Operator.

When I was in the project Noise Generation in our lab, I majorly dealt with the conditional/unconditional generative model synthesizing the seismic noise. After the project ended, I was involved in LSTM model development work and experiments sequential dataset synthesis in collaboration with the Department of Mechanical Engineering.

Now I’m interested in Neural Operator Learning. In particular, I focus on effective operator learning theoretically and practically. The goal is to bridge the gap between academia and industry in neural operator learning to create better neural operator models.