Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization (DiBO)
Published in ICML, 2025
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publications
Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization (CiBO)
Published in NeurIPS2025 Workshop on Structured Probabilisitic Inference & Generative Modeling (Oral), 2025
Diffusion Alignment as Variational Expectation-Maximization
Published in Preprint, 2025
Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
Published in Preprint, 2025
talks
Control as Probabilistic Inference
Published:
In this seminar hosted by KAIST’s System Intelligence Lab (SILAB), the talk focused on interpreting control problems through the lens of probabilistic inference.
Geometry-aware Posterior Inference for High dimensional black-box optimization
Published:
In this seminar hosted by KAIST’s System Intelligence Lab (SILAB), the talk focused on generative model based optimization on Riemannian Manifold.
teaching
Deep Learning Programming Study
Summer Lecture, Korea University, 2023
I served as a Teaching Assistant for the Deep Learning Programming Study under the guidance of Professor Sungbin Lim. In this role, I helped students master the fundamentals of building deep learning pipelines using advanced Python tools.
Teaching Assistant on IE343 Statistical Machine Learning
Undergraduate course, KAIST, Industrial & Systems Engineering, 2024
As a Teaching Assistant for the Statistical Machine Learning course (IE343) at KAIST, I support undergraduate students in developing a strong foundation in machine learning concepts and techniques.